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-
  • get_unique_classes() (in module cleanlab.internal.util) +
  • get_underperforming_clusters() (cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager method)
    • -
  • get_worst_cluster() (cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager method) +
  • get_unique_classes() (in module cleanlab.internal.util)
    • diff --git a/master/objects.inv b/master/objects.inv index 20de89e700042a59b56314dc80404e6470893451..eef5aeabda3ad4c644ebe4c21175a15df5f48bc1 100644 GIT binary patch delta 26857 zcmV)UK(N24t^%g60=@*?UZ@>`68QU+-Fg{!Sn>I{ zdhj7-zC$G}mZpal+;XLQSm9kQT-|69t>a~x^FBDe%;Kd@mr^y_$;XR#m$#oj{vBZH zgQ?F|K~2!c9_&?G>AI0%=qcZML?G+)1jZ^Kh@>T;G|H=TSCy(Sf0}h@G#XTw?mhf< zL;p})a7$nf@#+Pc;sELpxPD?-ZP;)K{1B(fDpr1g(-ygT!|+3aRv(Idf#<2?eO!1A zwA!MqoX_kMA?9sx5&`CIcoG2)&;V)Z`2Y>Di+i93*b`#@2G|o|{s!0+VBQAUZh(B~ z#^=2^K`HY5jZiMef2_?=F2bx0Q7(e-rYI~Ar@c8=Si_Cu1Rv>tRCh~66fO2Na;UZ5 zHHY#9Q^xpSu`-~jMpe+_pE&#JN@%$&vOPJwdUJbw`S$Yc&8N$oYxQoUkM#cY)u&6k z$>S4+tX@A}5RLrm5=F~AE8`@?QKZzhnyuWzhgsxcP zM|g<#+i;bLR%K6?$vQ5gWtJ)MZOZEMJ~_L-mQHYE>=pT*e2P{Gmq`|nZg0ClBC`TC zl!3v{1wy=9MZ6OHVeEG4qd)eGb(+WJ^PfB-RO|KNrn3tGTFbcF!AXOYFAHJ<@-~x` z3o!x|>XXI`!vVvSiVP$YebxmHb*&WIw~S1&rAtZKE#;HI3}FGulOhe0I@^wEM|-Xh zMW@f$6!4`6AVz34ixDB*Nk*#(!mIqb3%@-Y&p3KeEV1flR+B@|1_}?BL^ICdxA1(k 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Construct K nearest neighbours graph": [[93, "4.-Construct-K-nearest-neighbours-graph"]], "Near-duplicate issues": [[93, "Near-duplicate-issues"], [94, "Near-duplicate-issues"]], "Detecting Issues in a Text Dataset with Datalab": [[94, "Detecting-Issues-in-a-Text-Dataset-with-Datalab"]], "3. Define a classification model and compute out-of-sample predicted probabilities": [[94, "3.-Define-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find issues in your dataset": [[94, "4.-Use-cleanlab-to-find-issues-in-your-dataset"]], "Non-IID issues (data drift)": [[94, "Non-IID-issues-(data-drift)"]], "Miscellaneous workflows with Datalab": [[95, "Miscellaneous-workflows-with-Datalab"]], "Accelerate Issue Checks with Pre-computed kNN Graphs": [[95, "Accelerate-Issue-Checks-with-Pre-computed-kNN-Graphs"]], "1. Load and Prepare Your Dataset": [[95, "1.-Load-and-Prepare-Your-Dataset"]], "2. Compute kNN Graph": [[95, "2.-Compute-kNN-Graph"]], "3. Train a Classifier and Obtain Predicted Probabilities": [[95, "3.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"]], "4. Identify Data Issues Using Datalab": [[95, "4.-Identify-Data-Issues-Using-Datalab"]], "Explanation:": [[95, "Explanation:"]], "Data Valuation": [[95, "Data-Valuation"]], "1. Load and Prepare the Dataset": [[95, "1.-Load-and-Prepare-the-Dataset"], [95, "id2"], [95, "id5"]], "2. Vectorize the Text Data": [[95, "2.-Vectorize-the-Text-Data"]], "3. Perform Data Valuation with Datalab": [[95, "3.-Perform-Data-Valuation-with-Datalab"]], "4. (Optional) Visualize Data Valuation Scores": [[95, "4.-(Optional)-Visualize-Data-Valuation-Scores"]], "Find Underperforming Groups in a Dataset": [[95, "Find-Underperforming-Groups-in-a-Dataset"]], "1. Generate a Synthetic Dataset": [[95, "1.-Generate-a-Synthetic-Dataset"]], "2. Train a Classifier and Obtain Predicted Probabilities": [[95, "2.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"], [95, "id3"]], "3. (Optional) Cluster the Data": [[95, "3.-(Optional)-Cluster-the-Data"]], "4. Identify Underperforming Groups with Datalab": [[95, "4.-Identify-Underperforming-Groups-with-Datalab"], [95, "id4"]], "5. (Optional) Visualize the Results": [[95, "5.-(Optional)-Visualize-the-Results"]], "Predefining Data Slices for Detecting Underperforming Groups": [[95, "Predefining-Data-Slices-for-Detecting-Underperforming-Groups"]], "3. Define a Data Slice": [[95, "3.-Define-a-Data-Slice"]], "Detect if your dataset is non-IID": [[95, "Detect-if-your-dataset-is-non-IID"]], "2. Detect Non-IID Issues Using Datalab": [[95, "2.-Detect-Non-IID-Issues-Using-Datalab"]], "3. (Optional) Visualize the Results": [[95, "3.-(Optional)-Visualize-the-Results"]], "Catch Null Values in a Dataset": [[95, "Catch-Null-Values-in-a-Dataset"]], "1. Load the Dataset": [[95, "1.-Load-the-Dataset"], [95, "id8"]], "2: Encode Categorical Values": [[95, "2:-Encode-Categorical-Values"]], "3. Initialize Datalab": [[95, "3.-Initialize-Datalab"]], "4. Detect Null Values": [[95, "4.-Detect-Null-Values"]], "5. Sort the Dataset by Null Issues": [[95, "5.-Sort-the-Dataset-by-Null-Issues"]], "6. (Optional) Visualize the Results": [[95, "6.-(Optional)-Visualize-the-Results"]], "Detect class imbalance in your dataset": [[95, "Detect-class-imbalance-in-your-dataset"]], "1. Prepare data": [[95, "1.-Prepare-data"]], "2. Detect class imbalance with Datalab": [[95, "2.-Detect-class-imbalance-with-Datalab"]], "3. (Optional) Visualize class imbalance issues": [[95, "3.-(Optional)-Visualize-class-imbalance-issues"]], "Identify Spurious Correlations in Image Datasets": [[95, "Identify-Spurious-Correlations-in-Image-Datasets"]], "2. Run Datalab Analysis": [[95, "2.-Run-Datalab-Analysis"]], "3. Interpret the Results": [[95, "3.-Interpret-the-Results"]], "4. (Optional) Compare with a Dataset Without Spurious Correlations": [[95, "4.-(Optional)-Compare-with-a-Dataset-Without-Spurious-Correlations"]], "Understanding Dataset-level Labeling Issues": [[96, "Understanding-Dataset-level-Labeling-Issues"]], "Install dependencies and import them": [[96, "Install-dependencies-and-import-them"], [99, "Install-dependencies-and-import-them"]], "Fetch the data (can skip these details)": [[96, "Fetch-the-data-(can-skip-these-details)"]], "Start of tutorial: Evaluate the health of 8 popular datasets": [[96, "Start-of-tutorial:-Evaluate-the-health-of-8-popular-datasets"]], "FAQ": [[97, "FAQ"]], "What data can cleanlab detect issues in?": [[97, "What-data-can-cleanlab-detect-issues-in?"]], "How do I format classification labels for cleanlab?": [[97, "How-do-I-format-classification-labels-for-cleanlab?"]], "How do I infer the correct labels for examples cleanlab has flagged?": [[97, "How-do-I-infer-the-correct-labels-for-examples-cleanlab-has-flagged?"]], "How should I handle label errors in train vs. test data?": [[97, "How-should-I-handle-label-errors-in-train-vs.-test-data?"]], "How can I find label issues in big datasets with limited memory?": [[97, "How-can-I-find-label-issues-in-big-datasets-with-limited-memory?"]], "Why isn\u2019t CleanLearning working for me?": [[97, "Why-isn\u2019t-CleanLearning-working-for-me?"]], "How can I use different models for data cleaning vs. final training in CleanLearning?": [[97, "How-can-I-use-different-models-for-data-cleaning-vs.-final-training-in-CleanLearning?"]], "How do I hyperparameter tune only the final model trained (and not the one finding label issues) in CleanLearning?": [[97, "How-do-I-hyperparameter-tune-only-the-final-model-trained-(and-not-the-one-finding-label-issues)-in-CleanLearning?"]], "Why does regression.learn.CleanLearning take so long?": [[97, "Why-does-regression.learn.CleanLearning-take-so-long?"]], "How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?": [[97, "How-do-I-specify-pre-computed-data-slices/clusters-when-detecting-the-Underperforming-Group-Issue?"]], "How to handle near-duplicate data identified by Datalab?": [[97, "How-to-handle-near-duplicate-data-identified-by-Datalab?"]], "What ML models should I run cleanlab with? How do I fix the issues cleanlab has identified?": [[97, "What-ML-models-should-I-run-cleanlab-with?-How-do-I-fix-the-issues-cleanlab-has-identified?"]], "What license is cleanlab open-sourced under?": [[97, "What-license-is-cleanlab-open-sourced-under?"]], "Can\u2019t find an answer to your question?": [[97, "Can't-find-an-answer-to-your-question?"]], "Improving ML Performance via Data Curation with Train vs Test Splits": [[98, "Improving-ML-Performance-via-Data-Curation-with-Train-vs-Test-Splits"]], "Why did you make this tutorial?": [[98, "Why-did-you-make-this-tutorial?"]], "1. Install dependencies": [[98, "1.-Install-dependencies"]], "2. Preprocess the data": [[98, "2.-Preprocess-the-data"]], "3. Check for fundamental problems in the train/test setup": [[98, "3.-Check-for-fundamental-problems-in-the-train/test-setup"]], "4. Train model with original (noisy) training data": [[98, "4.-Train-model-with-original-(noisy)-training-data"]], "Compute out-of-sample predicted probabilities for the test data from this baseline model": [[98, "Compute-out-of-sample-predicted-probabilities-for-the-test-data-from-this-baseline-model"]], "5. Check for issues in test data and manually address them": [[98, "5.-Check-for-issues-in-test-data-and-manually-address-them"]], "Use clean test data to evaluate the performance of model trained on noisy training data": [[98, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-noisy-training-data"]], "6. Check for issues in training data and algorithmically correct them": [[98, "6.-Check-for-issues-in-training-data-and-algorithmically-correct-them"]], "7. Train model on cleaned training data": [[98, "7.-Train-model-on-cleaned-training-data"]], "Use clean test data to evaluate the performance of model trained on cleaned training data": [[98, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-cleaned-training-data"]], "8. Identifying better training data curation strategies via hyperparameter optimization techniques": [[98, "8.-Identifying-better-training-data-curation-strategies-via-hyperparameter-optimization-techniques"]], "9. Conclusion": [[98, "9.-Conclusion"]], "The Workflows of Data-centric AI for Classification with Noisy Labels": [[99, "The-Workflows-of-Data-centric-AI-for-Classification-with-Noisy-Labels"]], "Create the data (can skip these details)": [[99, "Create-the-data-(can-skip-these-details)"]], "Workflow 1: Use Datalab to detect many types of issues": [[99, "Workflow-1:-Use-Datalab-to-detect-many-types-of-issues"]], "Workflow 2: Use CleanLearning for more robust Machine Learning": [[99, "Workflow-2:-Use-CleanLearning-for-more-robust-Machine-Learning"]], "Clean Learning = Machine Learning with cleaned data": [[99, "Clean-Learning-=-Machine-Learning-with-cleaned-data"]], "Workflow 3: Use CleanLearning to find_label_issues in one line of code": [[99, "Workflow-3:-Use-CleanLearning-to-find_label_issues-in-one-line-of-code"]], "Visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[99, "Visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 4: Use cleanlab to find dataset-level and class-level issues": [[99, "Workflow-4:-Use-cleanlab-to-find-dataset-level-and-class-level-issues"]], "Now, let\u2019s see what happens if we merge classes \u201cseafoam green\u201d and \u201cyellow\u201d": [[99, "Now,-let's-see-what-happens-if-we-merge-classes-%22seafoam-green%22-and-%22yellow%22"]], "Workflow 5: Clean your test set too if you\u2019re doing ML with noisy labels!": [[99, "Workflow-5:-Clean-your-test-set-too-if-you're-doing-ML-with-noisy-labels!"]], "Workflow 6: One score to rule them all \u2013 use cleanlab\u2019s overall dataset health score": [[99, "Workflow-6:-One-score-to-rule-them-all----use-cleanlab's-overall-dataset-health-score"]], "How accurate is this dataset health score?": [[99, "How-accurate-is-this-dataset-health-score?"]], "Workflow(s) 7: Use count, rank, filter modules directly": [[99, "Workflow(s)-7:-Use-count,-rank,-filter-modules-directly"]], "Workflow 7.1 (count): Fully characterize label noise (noise matrix, joint, prior of true labels, \u2026)": [[99, "Workflow-7.1-(count):-Fully-characterize-label-noise-(noise-matrix,-joint,-prior-of-true-labels,-...)"]], "Use cleanlab to estimate and visualize the joint distribution of label noise and noise matrix of label flipping rates:": [[99, "Use-cleanlab-to-estimate-and-visualize-the-joint-distribution-of-label-noise-and-noise-matrix-of-label-flipping-rates:"]], "Workflow 7.2 (filter): Find label issues for any dataset and any model in one line of code": [[99, "Workflow-7.2-(filter):-Find-label-issues-for-any-dataset-and-any-model-in-one-line-of-code"]], "Again, we can visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[99, "Again,-we-can-visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 7.2 supports lots of methods to find_label_issues() via the filter_by parameter.": [[99, "Workflow-7.2-supports-lots-of-methods-to-find_label_issues()-via-the-filter_by-parameter."]], "Workflow 7.3 (rank): Automatically rank every example by a unique label quality score. Find errors using cleanlab.count.num_label_issues as a threshold.": [[99, "Workflow-7.3-(rank):-Automatically-rank-every-example-by-a-unique-label-quality-score.-Find-errors-using-cleanlab.count.num_label_issues-as-a-threshold."]], "Again, we can visualize the label issues found to see if Cleanlab works.": [[99, "Again,-we-can-visualize-the-label-issues-found-to-see-if-Cleanlab-works."]], "Not sure when to use Workflow 7.2 or 7.3 to find label issues?": [[99, "Not-sure-when-to-use-Workflow-7.2-or-7.3-to-find-label-issues?"]], "Workflow 8: Ensembling label quality scores from multiple predictors": [[99, "Workflow-8:-Ensembling-label-quality-scores-from-multiple-predictors"]], "Tutorials": [[100, "tutorials"]], "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators": [[101, "Estimate-Consensus-and-Annotator-Quality-for-Data-Labeled-by-Multiple-Annotators"]], "2. Create the data (can skip these details)": [[101, "2.-Create-the-data-(can-skip-these-details)"]], "3. Get initial consensus labels via majority vote and compute out-of-sample predicted probabilities": [[101, "3.-Get-initial-consensus-labels-via-majority-vote-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to get better consensus labels and other statistics": [[101, "4.-Use-cleanlab-to-get-better-consensus-labels-and-other-statistics"]], "Comparing improved consensus labels": [[101, "Comparing-improved-consensus-labels"]], "Inspecting consensus quality scores to find potential consensus label errors": [[101, "Inspecting-consensus-quality-scores-to-find-potential-consensus-label-errors"]], "5. Retrain model using improved consensus labels": [[101, "5.-Retrain-model-using-improved-consensus-labels"]], "Further improvements": [[101, "Further-improvements"]], "How does cleanlab.multiannotator work?": [[101, "How-does-cleanlab.multiannotator-work?"]], "Find Label Errors in Multi-Label Classification Datasets": [[102, "Find-Label-Errors-in-Multi-Label-Classification-Datasets"]], "1. Install required dependencies and get dataset": [[102, "1.-Install-required-dependencies-and-get-dataset"]], "2. Format data, labels, and model predictions": [[102, "2.-Format-data,-labels,-and-model-predictions"], [103, "2.-Format-data,-labels,-and-model-predictions"]], "3. Use cleanlab to find label issues": [[102, "3.-Use-cleanlab-to-find-label-issues"], [103, "3.-Use-cleanlab-to-find-label-issues"], [107, "3.-Use-cleanlab-to-find-label-issues"], [108, "3.-Use-cleanlab-to-find-label-issues"]], "Label quality scores": [[102, "Label-quality-scores"]], "Data issues beyond mislabeling (outliers, duplicates, drift, \u2026)": [[102, "Data-issues-beyond-mislabeling-(outliers,-duplicates,-drift,-...)"]], "How to format labels given as a one-hot (multi-hot) binary matrix?": [[102, "How-to-format-labels-given-as-a-one-hot-(multi-hot)-binary-matrix?"]], "Estimate label issues without Datalab": [[102, "Estimate-label-issues-without-Datalab"]], "Application to Real Data": [[102, "Application-to-Real-Data"]], "Finding Label Errors in Object Detection Datasets": [[103, "Finding-Label-Errors-in-Object-Detection-Datasets"]], "1. Install required dependencies and download data": [[103, "1.-Install-required-dependencies-and-download-data"], [107, "1.-Install-required-dependencies-and-download-data"], [108, "1.-Install-required-dependencies-and-download-data"]], "Get label quality scores": [[103, "Get-label-quality-scores"], [107, "Get-label-quality-scores"]], "4. Use ObjectLab to visualize label issues": [[103, "4.-Use-ObjectLab-to-visualize-label-issues"]], "Different kinds of label issues identified by ObjectLab": [[103, "Different-kinds-of-label-issues-identified-by-ObjectLab"]], "Other uses of visualize": [[103, "Other-uses-of-visualize"]], "Exploratory data analysis": [[103, "Exploratory-data-analysis"]], "Detect Outliers with Cleanlab and PyTorch Image Models (timm)": [[104, "Detect-Outliers-with-Cleanlab-and-PyTorch-Image-Models-(timm)"]], "1. Install the required dependencies": [[104, "1.-Install-the-required-dependencies"]], "2. Pre-process the Cifar10 dataset": [[104, "2.-Pre-process-the-Cifar10-dataset"]], "Visualize some of the training and test examples": [[104, "Visualize-some-of-the-training-and-test-examples"]], "3. Use cleanlab and feature embeddings to find outliers in the data": [[104, "3.-Use-cleanlab-and-feature-embeddings-to-find-outliers-in-the-data"]], "4. Use cleanlab and pred_probs to find outliers in the data": [[104, "4.-Use-cleanlab-and-pred_probs-to-find-outliers-in-the-data"]], "Computing Out-of-Sample Predicted Probabilities with Cross-Validation": [[105, "computing-out-of-sample-predicted-probabilities-with-cross-validation"]], "Out-of-sample predicted probabilities?": [[105, "out-of-sample-predicted-probabilities"]], "What is K-fold cross-validation?": [[105, "what-is-k-fold-cross-validation"]], "Find Noisy Labels in Regression Datasets": [[106, "Find-Noisy-Labels-in-Regression-Datasets"]], "3. Define a regression model and use cleanlab to find potential label errors": [[106, "3.-Define-a-regression-model-and-use-cleanlab-to-find-potential-label-errors"]], "5. Other ways to find noisy labels in regression datasets": [[106, "5.-Other-ways-to-find-noisy-labels-in-regression-datasets"]], "Find Label Errors in Semantic Segmentation Datasets": [[107, "Find-Label-Errors-in-Semantic-Segmentation-Datasets"]], "2. Get data, labels, and pred_probs": [[107, "2.-Get-data,-labels,-and-pred_probs"], [108, "2.-Get-data,-labels,-and-pred_probs"]], "Visualize top label issues": [[107, "Visualize-top-label-issues"]], "Classes which are commonly mislabeled overall": [[107, "Classes-which-are-commonly-mislabeled-overall"]], "Focusing on one specific class": [[107, "Focusing-on-one-specific-class"]], "Find Label Errors in Token Classification (Text) Datasets": [[108, "Find-Label-Errors-in-Token-Classification-(Text)-Datasets"]], "Most common word-level token mislabels": [[108, "Most-common-word-level-token-mislabels"]], "Find sentences containing a particular mislabeled word": [[108, "Find-sentences-containing-a-particular-mislabeled-word"]], "Sentence label quality score": [[108, "Sentence-label-quality-score"]], "How does cleanlab.token_classification work?": [[108, "How-does-cleanlab.token_classification-work?"]]}, "indexentries": {"cleanlab.benchmarking": [[0, "module-cleanlab.benchmarking"]], "module": 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"color_sentence() (in module cleanlab.internal.token_classification_utils)": [[56, "cleanlab.internal.token_classification_utils.color_sentence"]], "filter_sentence() (in module cleanlab.internal.token_classification_utils)": [[56, "cleanlab.internal.token_classification_utils.filter_sentence"]], "get_sentence() (in module cleanlab.internal.token_classification_utils)": [[56, "cleanlab.internal.token_classification_utils.get_sentence"]], "mapping() (in module cleanlab.internal.token_classification_utils)": [[56, "cleanlab.internal.token_classification_utils.mapping"]], "merge_probs() (in module cleanlab.internal.token_classification_utils)": [[56, "cleanlab.internal.token_classification_utils.merge_probs"]], "process_token() (in module cleanlab.internal.token_classification_utils)": [[56, "cleanlab.internal.token_classification_utils.process_token"]], "append_extra_datapoint() (in module cleanlab.internal.util)": [[57, "cleanlab.internal.util.append_extra_datapoint"]], 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Improve your data via many other techniques": [[83, "improve-your-data-via-many-other-techniques"]], "Contributing": [[83, "contributing"]], "Easy Mode": [[83, "easy-mode"], [91, "Easy-Mode"]], "How to migrate to versions >= 2.0.0 from pre 1.0.1": [[84, "how-to-migrate-to-versions-2-0-0-from-pre-1-0-1"]], "Function and class name changes": [[84, "function-and-class-name-changes"]], "Module name changes": [[84, "module-name-changes"]], "New modules": [[84, "new-modules"]], "Removed modules": [[84, "removed-modules"]], "Common argument and variable name changes": [[84, "common-argument-and-variable-name-changes"]], "CleanLearning Tutorials": [[85, "cleanlearning-tutorials"]], "Classification with Structured/Tabular Data and Noisy Labels": [[86, "Classification-with-Structured/Tabular-Data-and-Noisy-Labels"]], "1. Install required dependencies": [[86, "1.-Install-required-dependencies"], [87, "1.-Install-required-dependencies"], [93, "1.-Install-required-dependencies"], [94, "1.-Install-required-dependencies"], [106, "1.-Install-required-dependencies"]], "2. Load and process the data": [[86, "2.-Load-and-process-the-data"], [93, "2.-Load-and-process-the-data"], [106, "2.-Load-and-process-the-data"]], "3. Select a classification model and compute out-of-sample predicted probabilities": [[86, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"], [93, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find label issues": [[86, "4.-Use-cleanlab-to-find-label-issues"]], "5. Train a more robust model from noisy labels": [[86, "5.-Train-a-more-robust-model-from-noisy-labels"]], "Spending too much time on data quality?": [[86, "Spending-too-much-time-on-data-quality?"], [87, "Spending-too-much-time-on-data-quality?"], [90, "Spending-too-much-time-on-data-quality?"], [93, "Spending-too-much-time-on-data-quality?"], [94, "Spending-too-much-time-on-data-quality?"], [96, "Spending-too-much-time-on-data-quality?"], [99, "Spending-too-much-time-on-data-quality?"], [102, "Spending-too-much-time-on-data-quality?"], [104, "Spending-too-much-time-on-data-quality?"], [105, "spending-too-much-time-on-data-quality"], [106, "Spending-too-much-time-on-data-quality?"]], "Text Classification with Noisy Labels": [[87, "Text-Classification-with-Noisy-Labels"]], "2. Load and format the text dataset": [[87, "2.-Load-and-format-the-text-dataset"], [94, "2.-Load-and-format-the-text-dataset"]], "3. Define a classification model and use cleanlab to find potential label errors": [[87, "3.-Define-a-classification-model-and-use-cleanlab-to-find-potential-label-errors"]], "4. Train a more robust model from noisy labels": [[87, "4.-Train-a-more-robust-model-from-noisy-labels"], [106, "4.-Train-a-more-robust-model-from-noisy-labels"]], "Detecting Issues in an Audio Dataset with Datalab": [[88, "Detecting-Issues-in-an-Audio-Dataset-with-Datalab"]], "1. Install dependencies and import them": [[88, "1.-Install-dependencies-and-import-them"]], "2. Load the data": [[88, "2.-Load-the-data"]], "3. Use pre-trained SpeechBrain model to featurize audio": [[88, "3.-Use-pre-trained-SpeechBrain-model-to-featurize-audio"]], "4. Fit linear model and compute out-of-sample predicted probabilities": [[88, "4.-Fit-linear-model-and-compute-out-of-sample-predicted-probabilities"]], "5. Use cleanlab to find label issues": [[88, "5.-Use-cleanlab-to-find-label-issues"], [93, "5.-Use-cleanlab-to-find-label-issues"]], "Datalab: Advanced workflows to audit your data": [[89, "Datalab:-Advanced-workflows-to-audit-your-data"]], "Install and import required dependencies": [[89, "Install-and-import-required-dependencies"]], "Create and load the data": [[89, "Create-and-load-the-data"]], "Get out-of-sample predicted probabilities from a classifier": [[89, "Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "Instantiate Datalab object": [[89, "Instantiate-Datalab-object"]], "Functionality 1: Incremental issue search": [[89, "Functionality-1:-Incremental-issue-search"]], "Functionality 2: Specifying nondefault arguments": [[89, "Functionality-2:-Specifying-nondefault-arguments"]], "Functionality 3: Save and load Datalab objects": [[89, "Functionality-3:-Save-and-load-Datalab-objects"]], "Functionality 4: Adding a custom IssueManager": [[89, "Functionality-4:-Adding-a-custom-IssueManager"]], "Datalab: A unified audit to detect all kinds of issues in data and labels": [[90, "Datalab:-A-unified-audit-to-detect-all-kinds-of-issues-in-data-and-labels"]], "1. Install and import required dependencies": [[90, "1.-Install-and-import-required-dependencies"], [91, "1.-Install-and-import-required-dependencies"], [101, "1.-Install-and-import-required-dependencies"]], "2. Create and load the data (can skip these details)": [[90, "2.-Create-and-load-the-data-(can-skip-these-details)"]], "3. Get out-of-sample predicted probabilities from a classifier": [[90, "3.-Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "4. Use Datalab to find issues in the dataset": [[90, "4.-Use-Datalab-to-find-issues-in-the-dataset"]], "5. Learn more about the issues in your dataset": [[90, "5.-Learn-more-about-the-issues-in-your-dataset"]], "Get additional information": [[90, "Get-additional-information"]], "Near duplicate issues": [[90, "Near-duplicate-issues"], [91, "Near-duplicate-issues"]], "Detecting Issues in an Image Dataset with Datalab": [[91, "Detecting-Issues-in-an-Image-Dataset-with-Datalab"]], "2. Fetch and normalize the Fashion-MNIST dataset": [[91, "2.-Fetch-and-normalize-the-Fashion-MNIST-dataset"]], "3. Define a classification model": [[91, "3.-Define-a-classification-model"]], "4. Prepare the dataset for K-fold cross-validation": [[91, "4.-Prepare-the-dataset-for-K-fold-cross-validation"]], "5. Compute out-of-sample predicted probabilities and feature embeddings": [[91, "5.-Compute-out-of-sample-predicted-probabilities-and-feature-embeddings"]], "7. Use cleanlab to find issues": [[91, "7.-Use-cleanlab-to-find-issues"]], "View report": [[91, "View-report"]], "Label issues": [[91, "Label-issues"], [93, "Label-issues"], [94, "Label-issues"]], "View most likely examples with label errors": [[91, "View-most-likely-examples-with-label-errors"]], "Outlier issues": [[91, "Outlier-issues"], [93, "Outlier-issues"], [94, "Outlier-issues"]], "View most severe outliers": [[91, "View-most-severe-outliers"]], "View sets of near duplicate images": [[91, "View-sets-of-near-duplicate-images"]], "Dark images": [[91, "Dark-images"]], "View top examples of dark images": [[91, "View-top-examples-of-dark-images"]], "Low information images": [[91, "Low-information-images"]], "Datalab Tutorials": [[92, "datalab-tutorials"]], "Detecting Issues in Tabular Data\u00a0(Numeric/Categorical columns) with Datalab": [[93, "Detecting-Issues-in-Tabular-Data\u00a0(Numeric/Categorical-columns)-with-Datalab"]], "4. Construct K nearest neighbours graph": [[93, "4.-Construct-K-nearest-neighbours-graph"]], "Near-duplicate issues": [[93, "Near-duplicate-issues"], [94, "Near-duplicate-issues"]], "Detecting Issues in a Text Dataset with Datalab": [[94, "Detecting-Issues-in-a-Text-Dataset-with-Datalab"]], "3. Define a classification model and compute out-of-sample predicted probabilities": [[94, "3.-Define-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find issues in your dataset": [[94, "4.-Use-cleanlab-to-find-issues-in-your-dataset"]], "Non-IID issues (data drift)": [[94, "Non-IID-issues-(data-drift)"]], "Miscellaneous workflows with Datalab": [[95, "Miscellaneous-workflows-with-Datalab"]], "Accelerate Issue Checks with Pre-computed kNN Graphs": [[95, "Accelerate-Issue-Checks-with-Pre-computed-kNN-Graphs"]], "1. Load and Prepare Your Dataset": [[95, "1.-Load-and-Prepare-Your-Dataset"]], "2. Compute kNN Graph": [[95, "2.-Compute-kNN-Graph"]], "3. Train a Classifier and Obtain Predicted Probabilities": [[95, "3.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"]], "4. Identify Data Issues Using Datalab": [[95, "4.-Identify-Data-Issues-Using-Datalab"]], "Explanation:": [[95, "Explanation:"]], "Data Valuation": [[95, "Data-Valuation"]], "1. Load and Prepare the Dataset": [[95, "1.-Load-and-Prepare-the-Dataset"], [95, "id2"], [95, "id5"]], "2. Vectorize the Text Data": [[95, "2.-Vectorize-the-Text-Data"]], "3. Perform Data Valuation with Datalab": [[95, "3.-Perform-Data-Valuation-with-Datalab"]], "4. (Optional) Visualize Data Valuation Scores": [[95, "4.-(Optional)-Visualize-Data-Valuation-Scores"]], "Find Underperforming Groups in a Dataset": [[95, "Find-Underperforming-Groups-in-a-Dataset"]], "1. Generate a Synthetic Dataset": [[95, "1.-Generate-a-Synthetic-Dataset"]], "2. Train a Classifier and Obtain Predicted Probabilities": [[95, "2.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"], [95, "id3"]], "3. (Optional) Cluster the Data": [[95, "3.-(Optional)-Cluster-the-Data"]], "4. Identify Underperforming Groups with Datalab": [[95, "4.-Identify-Underperforming-Groups-with-Datalab"], [95, "id4"]], "5. (Optional) Visualize the Results": [[95, "5.-(Optional)-Visualize-the-Results"]], "Predefining Data Slices for Detecting Underperforming Groups": [[95, "Predefining-Data-Slices-for-Detecting-Underperforming-Groups"]], "3. Define a Data Slice": [[95, "3.-Define-a-Data-Slice"]], "Detect if your dataset is non-IID": [[95, "Detect-if-your-dataset-is-non-IID"]], "2. Detect Non-IID Issues Using Datalab": [[95, "2.-Detect-Non-IID-Issues-Using-Datalab"]], "3. (Optional) Visualize the Results": [[95, "3.-(Optional)-Visualize-the-Results"]], "Catch Null Values in a Dataset": [[95, "Catch-Null-Values-in-a-Dataset"]], "1. Load the Dataset": [[95, "1.-Load-the-Dataset"], [95, "id8"]], "2: Encode Categorical Values": [[95, "2:-Encode-Categorical-Values"]], "3. Initialize Datalab": [[95, "3.-Initialize-Datalab"]], "4. Detect Null Values": [[95, "4.-Detect-Null-Values"]], "5. Sort the Dataset by Null Issues": [[95, "5.-Sort-the-Dataset-by-Null-Issues"]], "6. (Optional) Visualize the Results": [[95, "6.-(Optional)-Visualize-the-Results"]], "Detect class imbalance in your dataset": [[95, "Detect-class-imbalance-in-your-dataset"]], "1. Prepare data": [[95, "1.-Prepare-data"]], "2. Detect class imbalance with Datalab": [[95, "2.-Detect-class-imbalance-with-Datalab"]], "3. (Optional) Visualize class imbalance issues": [[95, "3.-(Optional)-Visualize-class-imbalance-issues"]], "Identify Spurious Correlations in Image Datasets": [[95, "Identify-Spurious-Correlations-in-Image-Datasets"]], "2. Run Datalab Analysis": [[95, "2.-Run-Datalab-Analysis"]], "3. Interpret the Results": [[95, "3.-Interpret-the-Results"]], "4. (Optional) Compare with a Dataset Without Spurious Correlations": [[95, "4.-(Optional)-Compare-with-a-Dataset-Without-Spurious-Correlations"]], "Understanding Dataset-level Labeling Issues": [[96, "Understanding-Dataset-level-Labeling-Issues"]], "Install dependencies and import them": [[96, "Install-dependencies-and-import-them"], [99, "Install-dependencies-and-import-them"]], "Fetch the data (can skip these details)": [[96, "Fetch-the-data-(can-skip-these-details)"]], "Start of tutorial: Evaluate the health of 8 popular datasets": [[96, "Start-of-tutorial:-Evaluate-the-health-of-8-popular-datasets"]], "FAQ": [[97, "FAQ"]], "What data can cleanlab detect issues in?": [[97, "What-data-can-cleanlab-detect-issues-in?"]], "How do I format classification labels for cleanlab?": [[97, "How-do-I-format-classification-labels-for-cleanlab?"]], "How do I infer the correct labels for examples cleanlab has flagged?": [[97, "How-do-I-infer-the-correct-labels-for-examples-cleanlab-has-flagged?"]], "How should I handle label errors in train vs. test data?": [[97, "How-should-I-handle-label-errors-in-train-vs.-test-data?"]], "How can I find label issues in big datasets with limited memory?": [[97, "How-can-I-find-label-issues-in-big-datasets-with-limited-memory?"]], "Why isn\u2019t CleanLearning working for me?": [[97, "Why-isn\u2019t-CleanLearning-working-for-me?"]], "How can I use different models for data cleaning vs. final training in CleanLearning?": [[97, "How-can-I-use-different-models-for-data-cleaning-vs.-final-training-in-CleanLearning?"]], "How do I hyperparameter tune only the final model trained (and not the one finding label issues) in CleanLearning?": [[97, "How-do-I-hyperparameter-tune-only-the-final-model-trained-(and-not-the-one-finding-label-issues)-in-CleanLearning?"]], "Why does regression.learn.CleanLearning take so long?": [[97, "Why-does-regression.learn.CleanLearning-take-so-long?"]], "How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?": [[97, "How-do-I-specify-pre-computed-data-slices/clusters-when-detecting-the-Underperforming-Group-Issue?"]], "How to handle near-duplicate data identified by Datalab?": [[97, "How-to-handle-near-duplicate-data-identified-by-Datalab?"]], "What ML models should I run cleanlab with? How do I fix the issues cleanlab has identified?": [[97, "What-ML-models-should-I-run-cleanlab-with?-How-do-I-fix-the-issues-cleanlab-has-identified?"]], "What license is cleanlab open-sourced under?": [[97, "What-license-is-cleanlab-open-sourced-under?"]], "Can\u2019t find an answer to your question?": [[97, "Can't-find-an-answer-to-your-question?"]], "Improving ML Performance via Data Curation with Train vs Test Splits": [[98, "Improving-ML-Performance-via-Data-Curation-with-Train-vs-Test-Splits"]], "Why did you make this tutorial?": [[98, "Why-did-you-make-this-tutorial?"]], "1. Install dependencies": [[98, "1.-Install-dependencies"]], "2. Preprocess the data": [[98, "2.-Preprocess-the-data"]], "3. Check for fundamental problems in the train/test setup": [[98, "3.-Check-for-fundamental-problems-in-the-train/test-setup"]], "4. Train model with original (noisy) training data": [[98, "4.-Train-model-with-original-(noisy)-training-data"]], "Compute out-of-sample predicted probabilities for the test data from this baseline model": [[98, "Compute-out-of-sample-predicted-probabilities-for-the-test-data-from-this-baseline-model"]], "5. Check for issues in test data and manually address them": [[98, "5.-Check-for-issues-in-test-data-and-manually-address-them"]], "Use clean test data to evaluate the performance of model trained on noisy training data": [[98, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-noisy-training-data"]], "6. Check for issues in training data and algorithmically correct them": [[98, "6.-Check-for-issues-in-training-data-and-algorithmically-correct-them"]], "7. Train model on cleaned training data": [[98, "7.-Train-model-on-cleaned-training-data"]], "Use clean test data to evaluate the performance of model trained on cleaned training data": [[98, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-cleaned-training-data"]], "8. Identifying better training data curation strategies via hyperparameter optimization techniques": [[98, "8.-Identifying-better-training-data-curation-strategies-via-hyperparameter-optimization-techniques"]], "9. Conclusion": [[98, "9.-Conclusion"]], "The Workflows of Data-centric AI for Classification with Noisy Labels": [[99, "The-Workflows-of-Data-centric-AI-for-Classification-with-Noisy-Labels"]], "Create the data (can skip these details)": [[99, "Create-the-data-(can-skip-these-details)"]], "Workflow 1: Use Datalab to detect many types of issues": [[99, "Workflow-1:-Use-Datalab-to-detect-many-types-of-issues"]], "Workflow 2: Use CleanLearning for more robust Machine Learning": [[99, "Workflow-2:-Use-CleanLearning-for-more-robust-Machine-Learning"]], "Clean Learning = Machine Learning with cleaned data": [[99, "Clean-Learning-=-Machine-Learning-with-cleaned-data"]], "Workflow 3: Use CleanLearning to find_label_issues in one line of code": [[99, "Workflow-3:-Use-CleanLearning-to-find_label_issues-in-one-line-of-code"]], "Visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[99, "Visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 4: Use cleanlab to find dataset-level and class-level issues": [[99, "Workflow-4:-Use-cleanlab-to-find-dataset-level-and-class-level-issues"]], "Now, let\u2019s see what happens if we merge classes \u201cseafoam green\u201d and \u201cyellow\u201d": [[99, "Now,-let's-see-what-happens-if-we-merge-classes-%22seafoam-green%22-and-%22yellow%22"]], "Workflow 5: Clean your test set too if you\u2019re doing ML with noisy labels!": [[99, "Workflow-5:-Clean-your-test-set-too-if-you're-doing-ML-with-noisy-labels!"]], "Workflow 6: One score to rule them all \u2013 use cleanlab\u2019s overall dataset health score": [[99, "Workflow-6:-One-score-to-rule-them-all----use-cleanlab's-overall-dataset-health-score"]], "How accurate is this dataset health score?": [[99, "How-accurate-is-this-dataset-health-score?"]], "Workflow(s) 7: Use count, rank, filter modules directly": [[99, "Workflow(s)-7:-Use-count,-rank,-filter-modules-directly"]], "Workflow 7.1 (count): Fully characterize label noise (noise matrix, joint, prior of true labels, \u2026)": [[99, "Workflow-7.1-(count):-Fully-characterize-label-noise-(noise-matrix,-joint,-prior-of-true-labels,-...)"]], "Use cleanlab to estimate and visualize the joint distribution of label noise and noise matrix of label flipping rates:": [[99, "Use-cleanlab-to-estimate-and-visualize-the-joint-distribution-of-label-noise-and-noise-matrix-of-label-flipping-rates:"]], "Workflow 7.2 (filter): Find label issues for any dataset and any model in one line of code": [[99, "Workflow-7.2-(filter):-Find-label-issues-for-any-dataset-and-any-model-in-one-line-of-code"]], "Again, we can visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[99, "Again,-we-can-visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 7.2 supports lots of methods to find_label_issues() via the filter_by parameter.": [[99, "Workflow-7.2-supports-lots-of-methods-to-find_label_issues()-via-the-filter_by-parameter."]], "Workflow 7.3 (rank): Automatically rank every example by a unique label quality score. Find errors using cleanlab.count.num_label_issues as a threshold.": [[99, "Workflow-7.3-(rank):-Automatically-rank-every-example-by-a-unique-label-quality-score.-Find-errors-using-cleanlab.count.num_label_issues-as-a-threshold."]], "Again, we can visualize the label issues found to see if Cleanlab works.": [[99, "Again,-we-can-visualize-the-label-issues-found-to-see-if-Cleanlab-works."]], "Not sure when to use Workflow 7.2 or 7.3 to find label issues?": [[99, "Not-sure-when-to-use-Workflow-7.2-or-7.3-to-find-label-issues?"]], "Workflow 8: Ensembling label quality scores from multiple predictors": [[99, "Workflow-8:-Ensembling-label-quality-scores-from-multiple-predictors"]], "Tutorials": [[100, "tutorials"]], "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators": [[101, "Estimate-Consensus-and-Annotator-Quality-for-Data-Labeled-by-Multiple-Annotators"]], "2. Create the data (can skip these details)": [[101, "2.-Create-the-data-(can-skip-these-details)"]], "3. Get initial consensus labels via majority vote and compute out-of-sample predicted probabilities": [[101, "3.-Get-initial-consensus-labels-via-majority-vote-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to get better consensus labels and other statistics": [[101, "4.-Use-cleanlab-to-get-better-consensus-labels-and-other-statistics"]], "Comparing improved consensus labels": [[101, "Comparing-improved-consensus-labels"]], "Inspecting consensus quality scores to find potential consensus label errors": [[101, "Inspecting-consensus-quality-scores-to-find-potential-consensus-label-errors"]], "5. Retrain model using improved consensus labels": [[101, "5.-Retrain-model-using-improved-consensus-labels"]], "Further improvements": [[101, "Further-improvements"]], "How does cleanlab.multiannotator work?": [[101, "How-does-cleanlab.multiannotator-work?"]], "Find Label Errors in Multi-Label Classification Datasets": [[102, "Find-Label-Errors-in-Multi-Label-Classification-Datasets"]], "1. Install required dependencies and get dataset": [[102, "1.-Install-required-dependencies-and-get-dataset"]], "2. Format data, labels, and model predictions": [[102, "2.-Format-data,-labels,-and-model-predictions"], [103, "2.-Format-data,-labels,-and-model-predictions"]], "3. Use cleanlab to find label issues": [[102, "3.-Use-cleanlab-to-find-label-issues"], [103, "3.-Use-cleanlab-to-find-label-issues"], [107, "3.-Use-cleanlab-to-find-label-issues"], [108, "3.-Use-cleanlab-to-find-label-issues"]], "Label quality scores": [[102, "Label-quality-scores"]], "Data issues beyond mislabeling (outliers, duplicates, drift, \u2026)": [[102, "Data-issues-beyond-mislabeling-(outliers,-duplicates,-drift,-...)"]], "How to format labels given as a one-hot (multi-hot) binary matrix?": [[102, "How-to-format-labels-given-as-a-one-hot-(multi-hot)-binary-matrix?"]], "Estimate label issues without Datalab": [[102, "Estimate-label-issues-without-Datalab"]], "Application to Real Data": [[102, "Application-to-Real-Data"]], "Finding Label Errors in Object Detection Datasets": [[103, "Finding-Label-Errors-in-Object-Detection-Datasets"]], "1. Install required dependencies and download data": [[103, "1.-Install-required-dependencies-and-download-data"], [107, "1.-Install-required-dependencies-and-download-data"], [108, "1.-Install-required-dependencies-and-download-data"]], "Get label quality scores": [[103, "Get-label-quality-scores"], [107, "Get-label-quality-scores"]], "4. Use ObjectLab to visualize label issues": [[103, "4.-Use-ObjectLab-to-visualize-label-issues"]], "Different kinds of label issues identified by ObjectLab": [[103, "Different-kinds-of-label-issues-identified-by-ObjectLab"]], "Other uses of visualize": [[103, "Other-uses-of-visualize"]], "Exploratory data analysis": [[103, "Exploratory-data-analysis"]], "Detect Outliers with Cleanlab and PyTorch Image Models (timm)": [[104, "Detect-Outliers-with-Cleanlab-and-PyTorch-Image-Models-(timm)"]], "1. Install the required dependencies": [[104, "1.-Install-the-required-dependencies"]], "2. Pre-process the Cifar10 dataset": [[104, "2.-Pre-process-the-Cifar10-dataset"]], "Visualize some of the training and test examples": [[104, "Visualize-some-of-the-training-and-test-examples"]], "3. Use cleanlab and feature embeddings to find outliers in the data": [[104, "3.-Use-cleanlab-and-feature-embeddings-to-find-outliers-in-the-data"]], "4. Use cleanlab and pred_probs to find outliers in the data": [[104, "4.-Use-cleanlab-and-pred_probs-to-find-outliers-in-the-data"]], "Computing Out-of-Sample Predicted Probabilities with Cross-Validation": [[105, "computing-out-of-sample-predicted-probabilities-with-cross-validation"]], "Out-of-sample predicted probabilities?": [[105, "out-of-sample-predicted-probabilities"]], "What is K-fold cross-validation?": [[105, "what-is-k-fold-cross-validation"]], "Find Noisy Labels in Regression Datasets": [[106, "Find-Noisy-Labels-in-Regression-Datasets"]], "3. Define a regression model and use cleanlab to find potential label errors": [[106, "3.-Define-a-regression-model-and-use-cleanlab-to-find-potential-label-errors"]], "5. Other ways to find noisy labels in regression datasets": [[106, "5.-Other-ways-to-find-noisy-labels-in-regression-datasets"]], "Find Label Errors in Semantic Segmentation Datasets": [[107, "Find-Label-Errors-in-Semantic-Segmentation-Datasets"]], "2. Get data, labels, and pred_probs": [[107, "2.-Get-data,-labels,-and-pred_probs"], [108, "2.-Get-data,-labels,-and-pred_probs"]], "Visualize top label issues": [[107, "Visualize-top-label-issues"]], "Classes which are commonly mislabeled overall": [[107, "Classes-which-are-commonly-mislabeled-overall"]], "Focusing on one specific class": [[107, "Focusing-on-one-specific-class"]], "Find Label Errors in Token Classification (Text) Datasets": [[108, "Find-Label-Errors-in-Token-Classification-(Text)-Datasets"]], "Most common word-level token mislabels": [[108, "Most-common-word-level-token-mislabels"]], "Find sentences containing a particular mislabeled word": [[108, "Find-sentences-containing-a-particular-mislabeled-word"]], "Sentence label quality score": [[108, "Sentence-label-quality-score"]], "How does cleanlab.token_classification work?": [[108, "How-does-cleanlab.token_classification-work?"]]}, "indexentries": {"cleanlab.benchmarking": [[0, "module-cleanlab.benchmarking"]], "module": 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"cleanlab.internal.validation": [[58, "module-cleanlab.internal.validation"]], "labels_to_array() (in module cleanlab.internal.validation)": [[58, "cleanlab.internal.validation.labels_to_array"]], "labels_to_list_multilabel() (in module cleanlab.internal.validation)": [[58, "cleanlab.internal.validation.labels_to_list_multilabel"]], "cleanlab.models": [[59, "module-cleanlab.models"]], "keraswrappermodel (class in cleanlab.models.keras)": [[60, "cleanlab.models.keras.KerasWrapperModel"]], "keraswrappersequential (class in cleanlab.models.keras)": [[60, "cleanlab.models.keras.KerasWrapperSequential"]], "cleanlab.models.keras": [[60, "module-cleanlab.models.keras"]], "fit() (cleanlab.models.keras.keraswrappermodel method)": [[60, "cleanlab.models.keras.KerasWrapperModel.fit"]], "fit() (cleanlab.models.keras.keraswrappersequential method)": [[60, "cleanlab.models.keras.KerasWrapperSequential.fit"]], "get_params() (cleanlab.models.keras.keraswrappermodel method)": [[60, 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(cleanlab.models.keras.keraswrappermodel method)": [[60, "cleanlab.models.keras.KerasWrapperModel.summary"]], "summary() (cleanlab.models.keras.keraswrappersequential method)": [[60, "cleanlab.models.keras.KerasWrapperSequential.summary"]], "cleanlab.multiannotator": [[61, "module-cleanlab.multiannotator"]], "convert_long_to_wide_dataset() (in module cleanlab.multiannotator)": [[61, "cleanlab.multiannotator.convert_long_to_wide_dataset"]], "get_active_learning_scores() (in module cleanlab.multiannotator)": [[61, "cleanlab.multiannotator.get_active_learning_scores"]], "get_active_learning_scores_ensemble() (in module cleanlab.multiannotator)": [[61, "cleanlab.multiannotator.get_active_learning_scores_ensemble"]], "get_label_quality_multiannotator() (in module cleanlab.multiannotator)": [[61, "cleanlab.multiannotator.get_label_quality_multiannotator"]], "get_label_quality_multiannotator_ensemble() (in module cleanlab.multiannotator)": [[61, "cleanlab.multiannotator.get_label_quality_multiannotator_ensemble"]], "get_majority_vote_label() (in module cleanlab.multiannotator)": [[61, "cleanlab.multiannotator.get_majority_vote_label"]], "cleanlab.multilabel_classification.dataset": [[62, "module-cleanlab.multilabel_classification.dataset"]], "common_multilabel_issues() (in module cleanlab.multilabel_classification.dataset)": [[62, "cleanlab.multilabel_classification.dataset.common_multilabel_issues"]], "multilabel_health_summary() (in module cleanlab.multilabel_classification.dataset)": [[62, "cleanlab.multilabel_classification.dataset.multilabel_health_summary"]], "overall_multilabel_health_score() (in module cleanlab.multilabel_classification.dataset)": [[62, "cleanlab.multilabel_classification.dataset.overall_multilabel_health_score"]], "rank_classes_by_multilabel_quality() (in module cleanlab.multilabel_classification.dataset)": [[62, "cleanlab.multilabel_classification.dataset.rank_classes_by_multilabel_quality"]], "cleanlab.multilabel_classification.filter": [[63, "module-cleanlab.multilabel_classification.filter"]], "find_label_issues() (in module cleanlab.multilabel_classification.filter)": [[63, "cleanlab.multilabel_classification.filter.find_label_issues"]], "find_multilabel_issues_per_class() (in module cleanlab.multilabel_classification.filter)": [[63, "cleanlab.multilabel_classification.filter.find_multilabel_issues_per_class"]], "cleanlab.multilabel_classification": [[64, "module-cleanlab.multilabel_classification"]], "cleanlab.multilabel_classification.rank": [[65, "module-cleanlab.multilabel_classification.rank"]], "get_label_quality_scores() (in module cleanlab.multilabel_classification.rank)": [[65, "cleanlab.multilabel_classification.rank.get_label_quality_scores"]], "get_label_quality_scores_per_class() (in module cleanlab.multilabel_classification.rank)": [[65, "cleanlab.multilabel_classification.rank.get_label_quality_scores_per_class"]], "cleanlab.object_detection.filter": [[66, "module-cleanlab.object_detection.filter"]], "find_label_issues() (in module cleanlab.object_detection.filter)": [[66, "cleanlab.object_detection.filter.find_label_issues"]], "cleanlab.object_detection": [[67, "module-cleanlab.object_detection"]], "cleanlab.object_detection.rank": [[68, "module-cleanlab.object_detection.rank"]], "compute_badloc_box_scores() (in module cleanlab.object_detection.rank)": [[68, "cleanlab.object_detection.rank.compute_badloc_box_scores"]], "compute_overlooked_box_scores() (in module cleanlab.object_detection.rank)": [[68, "cleanlab.object_detection.rank.compute_overlooked_box_scores"]], "compute_swap_box_scores() (in module cleanlab.object_detection.rank)": [[68, "cleanlab.object_detection.rank.compute_swap_box_scores"]], "get_label_quality_scores() (in module cleanlab.object_detection.rank)": [[68, "cleanlab.object_detection.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.object_detection.rank)": [[68, "cleanlab.object_detection.rank.issues_from_scores"]], "pool_box_scores_per_image() (in module cleanlab.object_detection.rank)": [[68, "cleanlab.object_detection.rank.pool_box_scores_per_image"]], "bounding_box_size_distribution() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.bounding_box_size_distribution"]], "calculate_per_class_metrics() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.calculate_per_class_metrics"]], "class_label_distribution() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.class_label_distribution"]], "cleanlab.object_detection.summary": [[69, "module-cleanlab.object_detection.summary"]], "get_average_per_class_confusion_matrix() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.get_average_per_class_confusion_matrix"]], "get_sorted_bbox_count_idxs() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.get_sorted_bbox_count_idxs"]], "object_counts_per_image() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.object_counts_per_image"]], "plot_class_distribution() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.plot_class_distribution"]], "plot_class_size_distributions() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.plot_class_size_distributions"]], "visualize() (in module cleanlab.object_detection.summary)": [[69, "cleanlab.object_detection.summary.visualize"]], "outofdistribution (class in cleanlab.outlier)": [[70, "cleanlab.outlier.OutOfDistribution"]], "cleanlab.outlier": [[70, "module-cleanlab.outlier"]], "fit() (cleanlab.outlier.outofdistribution method)": [[70, "cleanlab.outlier.OutOfDistribution.fit"]], "fit_score() (cleanlab.outlier.outofdistribution method)": [[70, "cleanlab.outlier.OutOfDistribution.fit_score"]], "score() (cleanlab.outlier.outofdistribution method)": [[70, "cleanlab.outlier.OutOfDistribution.score"]], "cleanlab.rank": [[71, "module-cleanlab.rank"]], "find_top_issues() (in module cleanlab.rank)": [[71, "cleanlab.rank.find_top_issues"]], "get_confidence_weighted_entropy_for_each_label() (in module cleanlab.rank)": [[71, "cleanlab.rank.get_confidence_weighted_entropy_for_each_label"]], "get_label_quality_ensemble_scores() (in module cleanlab.rank)": [[71, "cleanlab.rank.get_label_quality_ensemble_scores"]], "get_label_quality_scores() (in module cleanlab.rank)": [[71, "cleanlab.rank.get_label_quality_scores"]], "get_normalized_margin_for_each_label() (in module cleanlab.rank)": [[71, "cleanlab.rank.get_normalized_margin_for_each_label"]], "get_self_confidence_for_each_label() (in module cleanlab.rank)": [[71, "cleanlab.rank.get_self_confidence_for_each_label"]], "order_label_issues() (in module cleanlab.rank)": [[71, "cleanlab.rank.order_label_issues"]], "cleanlab.regression": [[72, "module-cleanlab.regression"]], "cleanlearning (class in cleanlab.regression.learn)": [[73, "cleanlab.regression.learn.CleanLearning"]], "__init_subclass__() (cleanlab.regression.learn.cleanlearning class method)": [[73, "cleanlab.regression.learn.CleanLearning.__init_subclass__"]], "cleanlab.regression.learn": [[73, "module-cleanlab.regression.learn"]], "find_label_issues() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.find_label_issues"]], "fit() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.fit"]], "get_aleatoric_uncertainty() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.get_aleatoric_uncertainty"]], "get_epistemic_uncertainty() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.get_epistemic_uncertainty"]], "get_label_issues() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.get_label_issues"]], "get_metadata_routing() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.get_metadata_routing"]], "get_params() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.get_params"]], "predict() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.predict"]], "save_space() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.save_space"]], "score() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.score"]], "set_fit_request() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.set_fit_request"]], "set_params() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.set_params"]], "set_score_request() (cleanlab.regression.learn.cleanlearning method)": [[73, "cleanlab.regression.learn.CleanLearning.set_score_request"]], "cleanlab.regression.rank": [[74, "module-cleanlab.regression.rank"]], "get_label_quality_scores() (in module cleanlab.regression.rank)": [[74, "cleanlab.regression.rank.get_label_quality_scores"]], "cleanlab.segmentation.filter": [[75, "module-cleanlab.segmentation.filter"]], "find_label_issues() (in module cleanlab.segmentation.filter)": [[75, "cleanlab.segmentation.filter.find_label_issues"]], "cleanlab.segmentation": [[76, "module-cleanlab.segmentation"]], "cleanlab.segmentation.rank": [[77, "module-cleanlab.segmentation.rank"]], "get_label_quality_scores() (in module cleanlab.segmentation.rank)": [[77, "cleanlab.segmentation.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.segmentation.rank)": [[77, "cleanlab.segmentation.rank.issues_from_scores"]], "cleanlab.segmentation.summary": [[78, "module-cleanlab.segmentation.summary"]], "common_label_issues() (in module cleanlab.segmentation.summary)": [[78, "cleanlab.segmentation.summary.common_label_issues"]], "display_issues() (in module cleanlab.segmentation.summary)": [[78, "cleanlab.segmentation.summary.display_issues"]], "filter_by_class() (in module cleanlab.segmentation.summary)": [[78, "cleanlab.segmentation.summary.filter_by_class"]], "cleanlab.token_classification.filter": [[79, "module-cleanlab.token_classification.filter"]], "find_label_issues() (in module cleanlab.token_classification.filter)": [[79, "cleanlab.token_classification.filter.find_label_issues"]], "cleanlab.token_classification": [[80, "module-cleanlab.token_classification"]], "cleanlab.token_classification.rank": [[81, "module-cleanlab.token_classification.rank"]], "get_label_quality_scores() (in module cleanlab.token_classification.rank)": [[81, "cleanlab.token_classification.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.token_classification.rank)": [[81, "cleanlab.token_classification.rank.issues_from_scores"]], "cleanlab.token_classification.summary": [[82, "module-cleanlab.token_classification.summary"]], "common_label_issues() (in module cleanlab.token_classification.summary)": [[82, "cleanlab.token_classification.summary.common_label_issues"]], "display_issues() (in module cleanlab.token_classification.summary)": [[82, "cleanlab.token_classification.summary.display_issues"]], "filter_by_token() (in module cleanlab.token_classification.summary)": [[82, "cleanlab.token_classification.summary.filter_by_token"]]}}) \ No newline at end of file diff --git a/master/tutorials/clean_learning/tabular.ipynb b/master/tutorials/clean_learning/tabular.ipynb index 035a453c2..5e784d0c6 100644 --- a/master/tutorials/clean_learning/tabular.ipynb +++ b/master/tutorials/clean_learning/tabular.ipynb @@ -113,10 +113,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:41.701646Z", - "iopub.status.busy": "2024-08-12T18:53:41.701187Z", - "iopub.status.idle": "2024-08-12T18:53:43.282413Z", - "shell.execute_reply": "2024-08-12T18:53:43.281715Z" + "iopub.execute_input": "2024-08-15T19:27:32.175444Z", + "iopub.status.busy": "2024-08-15T19:27:32.175099Z", + "iopub.status.idle": "2024-08-15T19:27:33.655324Z", + "shell.execute_reply": "2024-08-15T19:27:33.654740Z" }, "nbsphinx": "hidden" }, @@ -126,7 +126,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -151,10 +151,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:43.285416Z", - "iopub.status.busy": "2024-08-12T18:53:43.285068Z", - "iopub.status.idle": "2024-08-12T18:53:43.306423Z", - "shell.execute_reply": "2024-08-12T18:53:43.305786Z" + "iopub.execute_input": "2024-08-15T19:27:33.658284Z", + "iopub.status.busy": "2024-08-15T19:27:33.657612Z", + "iopub.status.idle": "2024-08-15T19:27:33.676622Z", + "shell.execute_reply": "2024-08-15T19:27:33.676082Z" } }, "outputs": [], @@ -195,10 +195,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:43.309404Z", - "iopub.status.busy": "2024-08-12T18:53:43.308901Z", - "iopub.status.idle": "2024-08-12T18:53:43.590676Z", - "shell.execute_reply": "2024-08-12T18:53:43.590074Z" + "iopub.execute_input": "2024-08-15T19:27:33.678883Z", + "iopub.status.busy": "2024-08-15T19:27:33.678472Z", + "iopub.status.idle": "2024-08-15T19:27:33.873449Z", + "shell.execute_reply": "2024-08-15T19:27:33.872840Z" } }, "outputs": [ @@ -305,10 +305,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:43.622837Z", - "iopub.status.busy": "2024-08-12T18:53:43.622392Z", - "iopub.status.idle": "2024-08-12T18:53:43.626532Z", - "shell.execute_reply": "2024-08-12T18:53:43.626050Z" + "iopub.execute_input": "2024-08-15T19:27:33.903610Z", + "iopub.status.busy": "2024-08-15T19:27:33.903202Z", + "iopub.status.idle": "2024-08-15T19:27:33.906628Z", + "shell.execute_reply": "2024-08-15T19:27:33.906168Z" } }, "outputs": [], @@ -329,10 +329,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:43.628660Z", - "iopub.status.busy": "2024-08-12T18:53:43.628290Z", - "iopub.status.idle": "2024-08-12T18:53:43.636581Z", - "shell.execute_reply": "2024-08-12T18:53:43.636072Z" + "iopub.execute_input": "2024-08-15T19:27:33.908779Z", + "iopub.status.busy": "2024-08-15T19:27:33.908450Z", + "iopub.status.idle": "2024-08-15T19:27:33.916596Z", + "shell.execute_reply": "2024-08-15T19:27:33.916032Z" } }, "outputs": [], @@ -384,10 +384,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:43.638906Z", - "iopub.status.busy": "2024-08-12T18:53:43.638534Z", - "iopub.status.idle": "2024-08-12T18:53:43.641123Z", - "shell.execute_reply": "2024-08-12T18:53:43.640620Z" + "iopub.execute_input": "2024-08-15T19:27:33.918799Z", + "iopub.status.busy": "2024-08-15T19:27:33.918620Z", + "iopub.status.idle": "2024-08-15T19:27:33.921313Z", + "shell.execute_reply": "2024-08-15T19:27:33.920844Z" } }, "outputs": [], @@ -409,10 +409,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:43.643076Z", - "iopub.status.busy": "2024-08-12T18:53:43.642762Z", - "iopub.status.idle": "2024-08-12T18:53:44.178834Z", - "shell.execute_reply": "2024-08-12T18:53:44.178253Z" + "iopub.execute_input": "2024-08-15T19:27:33.923111Z", + "iopub.status.busy": "2024-08-15T19:27:33.922936Z", + "iopub.status.idle": "2024-08-15T19:27:34.437568Z", + "shell.execute_reply": "2024-08-15T19:27:34.437032Z" } }, "outputs": [], @@ -446,10 +446,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:44.181632Z", - "iopub.status.busy": "2024-08-12T18:53:44.181238Z", - "iopub.status.idle": "2024-08-12T18:53:46.388740Z", - "shell.execute_reply": "2024-08-12T18:53:46.388108Z" + "iopub.execute_input": "2024-08-15T19:27:34.439919Z", + "iopub.status.busy": "2024-08-15T19:27:34.439733Z", + "iopub.status.idle": "2024-08-15T19:27:36.488622Z", + "shell.execute_reply": "2024-08-15T19:27:36.487989Z" } }, "outputs": [ @@ -481,10 +481,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:46.391610Z", - "iopub.status.busy": "2024-08-12T18:53:46.390811Z", - "iopub.status.idle": "2024-08-12T18:53:46.401301Z", - "shell.execute_reply": "2024-08-12T18:53:46.400756Z" + "iopub.execute_input": "2024-08-15T19:27:36.491442Z", + "iopub.status.busy": "2024-08-15T19:27:36.490628Z", + "iopub.status.idle": "2024-08-15T19:27:36.501144Z", + "shell.execute_reply": "2024-08-15T19:27:36.500707Z" } }, "outputs": [ @@ -605,10 +605,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:46.403503Z", - "iopub.status.busy": "2024-08-12T18:53:46.403168Z", - "iopub.status.idle": "2024-08-12T18:53:46.407486Z", - "shell.execute_reply": "2024-08-12T18:53:46.406942Z" + "iopub.execute_input": "2024-08-15T19:27:36.503355Z", + "iopub.status.busy": "2024-08-15T19:27:36.502909Z", + "iopub.status.idle": "2024-08-15T19:27:36.506883Z", + "shell.execute_reply": "2024-08-15T19:27:36.506329Z" } }, "outputs": [], @@ -633,10 +633,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:46.409604Z", - "iopub.status.busy": "2024-08-12T18:53:46.409263Z", - "iopub.status.idle": "2024-08-12T18:53:46.416637Z", - "shell.execute_reply": "2024-08-12T18:53:46.416174Z" + "iopub.execute_input": "2024-08-15T19:27:36.508909Z", + "iopub.status.busy": "2024-08-15T19:27:36.508598Z", + "iopub.status.idle": "2024-08-15T19:27:36.515533Z", + "shell.execute_reply": "2024-08-15T19:27:36.515090Z" } }, "outputs": [], @@ -658,10 +658,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:46.418720Z", - "iopub.status.busy": "2024-08-12T18:53:46.418378Z", - "iopub.status.idle": "2024-08-12T18:53:46.535003Z", - "shell.execute_reply": "2024-08-12T18:53:46.534438Z" + "iopub.execute_input": "2024-08-15T19:27:36.517527Z", + "iopub.status.busy": "2024-08-15T19:27:36.517180Z", + "iopub.status.idle": "2024-08-15T19:27:36.629610Z", + "shell.execute_reply": "2024-08-15T19:27:36.629050Z" } }, "outputs": [ @@ -691,10 +691,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:46.537339Z", - "iopub.status.busy": "2024-08-12T18:53:46.536944Z", - "iopub.status.idle": "2024-08-12T18:53:46.539790Z", - "shell.execute_reply": "2024-08-12T18:53:46.539324Z" + "iopub.execute_input": "2024-08-15T19:27:36.631718Z", + "iopub.status.busy": "2024-08-15T19:27:36.631278Z", + "iopub.status.idle": "2024-08-15T19:27:36.634138Z", + "shell.execute_reply": "2024-08-15T19:27:36.633600Z" } }, "outputs": [], @@ -715,10 +715,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:46.541970Z", - "iopub.status.busy": "2024-08-12T18:53:46.541632Z", - "iopub.status.idle": "2024-08-12T18:53:48.807764Z", - "shell.execute_reply": "2024-08-12T18:53:48.807088Z" + "iopub.execute_input": "2024-08-15T19:27:36.636064Z", + "iopub.status.busy": "2024-08-15T19:27:36.635797Z", + "iopub.status.idle": "2024-08-15T19:27:38.770424Z", + "shell.execute_reply": "2024-08-15T19:27:38.769614Z" } }, "outputs": [], @@ -738,10 +738,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:48.811078Z", - "iopub.status.busy": "2024-08-12T18:53:48.810181Z", - "iopub.status.idle": "2024-08-12T18:53:48.822087Z", - "shell.execute_reply": "2024-08-12T18:53:48.821596Z" + "iopub.execute_input": "2024-08-15T19:27:38.773797Z", + "iopub.status.busy": "2024-08-15T19:27:38.772969Z", + "iopub.status.idle": "2024-08-15T19:27:38.784753Z", + "shell.execute_reply": "2024-08-15T19:27:38.784189Z" } }, "outputs": [ @@ -786,10 +786,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:48.824275Z", - "iopub.status.busy": "2024-08-12T18:53:48.823917Z", - "iopub.status.idle": "2024-08-12T18:53:49.001638Z", - "shell.execute_reply": "2024-08-12T18:53:49.001079Z" + "iopub.execute_input": "2024-08-15T19:27:38.787133Z", + "iopub.status.busy": "2024-08-15T19:27:38.786655Z", + "iopub.status.idle": "2024-08-15T19:27:38.842380Z", + "shell.execute_reply": "2024-08-15T19:27:38.841820Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/clean_learning/text.html b/master/tutorials/clean_learning/text.html index 5df852fb0..69234e81b 100644 --- a/master/tutorials/clean_learning/text.html +++ b/master/tutorials/clean_learning/text.html @@ -817,7 +817,7 @@

    2. Load and format the text dataset 
     This dataset has 10 classes.
-Classes: {'visa_or_mastercard', 'cancel_transfer', 'change_pin', 'lost_or_stolen_phone', 'card_payment_fee_charged', 'getting_spare_card', 'beneficiary_not_allowed', 'apple_pay_or_google_pay', 'card_about_to_expire', 'supported_cards_and_currencies'}
+Classes: {'getting_spare_card', 'lost_or_stolen_phone', 'supported_cards_and_currencies', 'visa_or_mastercard', 'card_about_to_expire', 'card_payment_fee_charged', 'apple_pay_or_google_pay', 'cancel_transfer', 'change_pin', 'beneficiary_not_allowed'}

    Let’s print the first example in the train set.

    @@ -880,43 +880,43 @@

    2. Load and format the text dataset
    -
    +
    -
    +
    -
    +
    -
    +
    -
    +
    -
    +
    -
    +
    @@ -1219,7 +1219,7 @@

    Spending too much time on data quality?Cleanlab Studio – an automated platform to find and fix issues in your dataset, 100x faster and more accurately. Cleanlab Studio automatically runs optimized data quality algorithms from this package on top of cutting-edge AutoML & Foundation models fit to your data, and helps you fix detected issues via a smart data correction interface. Try it for free!

    The modern AI pipeline automated with Cleanlab Studio

    diff --git a/master/tutorials/clean_learning/text.ipynb b/master/tutorials/clean_learning/text.ipynb index 001a213a7..249aadb2b 100644 --- a/master/tutorials/clean_learning/text.ipynb +++ b/master/tutorials/clean_learning/text.ipynb @@ -115,10 +115,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:52.248151Z", - "iopub.status.busy": "2024-08-12T18:53:52.247987Z", - "iopub.status.idle": "2024-08-12T18:53:55.894101Z", - "shell.execute_reply": "2024-08-12T18:53:55.893473Z" + "iopub.execute_input": "2024-08-15T19:27:42.558639Z", + "iopub.status.busy": "2024-08-15T19:27:42.558470Z", + "iopub.status.idle": "2024-08-15T19:27:45.876667Z", + "shell.execute_reply": "2024-08-15T19:27:45.876117Z" }, "nbsphinx": "hidden" }, @@ -135,7 +135,7 @@ "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\" # disable parallelism to avoid deadlocks with huggingface\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -160,10 +160,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:55.896748Z", - "iopub.status.busy": "2024-08-12T18:53:55.896431Z", - "iopub.status.idle": "2024-08-12T18:53:55.900025Z", - "shell.execute_reply": "2024-08-12T18:53:55.899460Z" + "iopub.execute_input": "2024-08-15T19:27:45.879087Z", + "iopub.status.busy": "2024-08-15T19:27:45.878772Z", + "iopub.status.idle": "2024-08-15T19:27:45.882150Z", + "shell.execute_reply": "2024-08-15T19:27:45.881613Z" } }, "outputs": [], @@ -185,10 +185,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:55.901985Z", - "iopub.status.busy": "2024-08-12T18:53:55.901681Z", - "iopub.status.idle": "2024-08-12T18:53:55.904870Z", - "shell.execute_reply": "2024-08-12T18:53:55.904262Z" + "iopub.execute_input": "2024-08-15T19:27:45.884279Z", + "iopub.status.busy": "2024-08-15T19:27:45.883881Z", + "iopub.status.idle": "2024-08-15T19:27:45.887053Z", + "shell.execute_reply": "2024-08-15T19:27:45.886505Z" }, "nbsphinx": "hidden" }, @@ -219,10 +219,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:55.906806Z", - "iopub.status.busy": "2024-08-12T18:53:55.906507Z", - "iopub.status.idle": "2024-08-12T18:53:56.076228Z", - "shell.execute_reply": "2024-08-12T18:53:56.075627Z" + "iopub.execute_input": "2024-08-15T19:27:45.889108Z", + "iopub.status.busy": "2024-08-15T19:27:45.888664Z", + "iopub.status.idle": "2024-08-15T19:27:45.942599Z", + "shell.execute_reply": "2024-08-15T19:27:45.942052Z" } }, "outputs": [ @@ -312,10 +312,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:56.078447Z", - "iopub.status.busy": "2024-08-12T18:53:56.078088Z", - "iopub.status.idle": "2024-08-12T18:53:56.081709Z", - "shell.execute_reply": "2024-08-12T18:53:56.081260Z" + "iopub.execute_input": "2024-08-15T19:27:45.944734Z", + "iopub.status.busy": "2024-08-15T19:27:45.944391Z", + "iopub.status.idle": "2024-08-15T19:27:45.947974Z", + "shell.execute_reply": "2024-08-15T19:27:45.947514Z" } }, "outputs": [], @@ -330,10 +330,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:56.083777Z", - "iopub.status.busy": "2024-08-12T18:53:56.083428Z", - "iopub.status.idle": "2024-08-12T18:53:56.086941Z", - "shell.execute_reply": "2024-08-12T18:53:56.086476Z" + "iopub.execute_input": "2024-08-15T19:27:45.949985Z", + "iopub.status.busy": "2024-08-15T19:27:45.949666Z", + "iopub.status.idle": "2024-08-15T19:27:45.953173Z", + "shell.execute_reply": "2024-08-15T19:27:45.952721Z" } }, "outputs": [ @@ -342,7 +342,7 @@ "output_type": "stream", "text": [ "This dataset has 10 classes.\n", - "Classes: {'visa_or_mastercard', 'cancel_transfer', 'change_pin', 'lost_or_stolen_phone', 'card_payment_fee_charged', 'getting_spare_card', 'beneficiary_not_allowed', 'apple_pay_or_google_pay', 'card_about_to_expire', 'supported_cards_and_currencies'}\n" + "Classes: {'getting_spare_card', 'lost_or_stolen_phone', 'supported_cards_and_currencies', 'visa_or_mastercard', 'card_about_to_expire', 'card_payment_fee_charged', 'apple_pay_or_google_pay', 'cancel_transfer', 'change_pin', 'beneficiary_not_allowed'}\n" ] } ], @@ -365,10 +365,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:56.088941Z", - "iopub.status.busy": "2024-08-12T18:53:56.088604Z", - "iopub.status.idle": "2024-08-12T18:53:56.091760Z", - "shell.execute_reply": "2024-08-12T18:53:56.091308Z" + "iopub.execute_input": "2024-08-15T19:27:45.955186Z", + "iopub.status.busy": "2024-08-15T19:27:45.954879Z", + "iopub.status.idle": "2024-08-15T19:27:45.957998Z", + "shell.execute_reply": "2024-08-15T19:27:45.957466Z" } }, "outputs": [ @@ -409,10 +409,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:56.093930Z", - "iopub.status.busy": "2024-08-12T18:53:56.093483Z", - "iopub.status.idle": "2024-08-12T18:53:56.096951Z", - "shell.execute_reply": "2024-08-12T18:53:56.096394Z" + "iopub.execute_input": "2024-08-15T19:27:45.960193Z", + "iopub.status.busy": "2024-08-15T19:27:45.959764Z", + "iopub.status.idle": "2024-08-15T19:27:45.963125Z", + "shell.execute_reply": "2024-08-15T19:27:45.962546Z" } }, "outputs": [], @@ -453,17 +453,17 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:53:56.098867Z", - "iopub.status.busy": "2024-08-12T18:53:56.098591Z", - "iopub.status.idle": "2024-08-12T18:54:01.596872Z", - "shell.execute_reply": "2024-08-12T18:54:01.596260Z" + "iopub.execute_input": "2024-08-15T19:27:45.965041Z", + "iopub.status.busy": "2024-08-15T19:27:45.964733Z", + "iopub.status.idle": "2024-08-15T19:27:50.230959Z", + "shell.execute_reply": "2024-08-15T19:27:50.230392Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5fce0f83ffcb45b1b4e91907422e2fd5", + "model_id": "18e1dd389279416b9826a2293eec395e", "version_major": 2, "version_minor": 0 }, @@ -477,7 +477,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8220af5113534a53bc94d0f5c8251a66", + "model_id": "f0dd1debaaf34981aa3e55254958ee72", "version_major": 2, "version_minor": 0 }, @@ -491,7 +491,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "399a7f37c7aa40b58c950e18df0b5960", + "model_id": "bc18025481124500a65d4cf4f8fd81cb", "version_major": 2, "version_minor": 0 }, @@ -505,7 +505,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "49e67bb21955496ba2eee2c0e6dad0ab", + "model_id": "d098387e1f8d4bfbb22cbd40f5b8e0fa", "version_major": 2, "version_minor": 0 }, @@ -519,7 +519,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "289a07c93d8049998a1f7e65320f71c8", + "model_id": "5904a3de384844e5aac5db1ba56ac44f", "version_major": 2, "version_minor": 0 }, @@ -533,7 +533,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a94fae83aa2341e5b8d1ae56f3b7cbda", + "model_id": "105deb524a014f529ced54724d1d08a6", "version_major": 2, "version_minor": 0 }, @@ -547,7 +547,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b2f79098c4674c5ca353b28833562218", + "model_id": "f5cd8fbfe34b4c5c895a38fe30e7362c", "version_major": 2, "version_minor": 0 }, @@ -601,10 +601,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:01.600043Z", - "iopub.status.busy": "2024-08-12T18:54:01.599613Z", - "iopub.status.idle": "2024-08-12T18:54:01.602661Z", - "shell.execute_reply": "2024-08-12T18:54:01.602180Z" + "iopub.execute_input": "2024-08-15T19:27:50.233659Z", + "iopub.status.busy": "2024-08-15T19:27:50.233275Z", + "iopub.status.idle": "2024-08-15T19:27:50.236294Z", + "shell.execute_reply": "2024-08-15T19:27:50.235798Z" } }, "outputs": [], @@ -626,10 +626,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:01.604735Z", - "iopub.status.busy": "2024-08-12T18:54:01.604395Z", - "iopub.status.idle": "2024-08-12T18:54:01.606950Z", - "shell.execute_reply": "2024-08-12T18:54:01.606508Z" + "iopub.execute_input": "2024-08-15T19:27:50.238340Z", + "iopub.status.busy": "2024-08-15T19:27:50.238008Z", + "iopub.status.idle": "2024-08-15T19:27:50.240555Z", + "shell.execute_reply": "2024-08-15T19:27:50.240110Z" } }, "outputs": [], @@ -644,10 +644,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:01.608945Z", - "iopub.status.busy": "2024-08-12T18:54:01.608609Z", - "iopub.status.idle": "2024-08-12T18:54:04.445747Z", - "shell.execute_reply": "2024-08-12T18:54:04.444939Z" + "iopub.execute_input": "2024-08-15T19:27:50.242583Z", + "iopub.status.busy": "2024-08-15T19:27:50.242263Z", + "iopub.status.idle": "2024-08-15T19:27:52.943233Z", + "shell.execute_reply": "2024-08-15T19:27:52.942408Z" }, "scrolled": true }, @@ -670,10 +670,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:04.449080Z", - "iopub.status.busy": "2024-08-12T18:54:04.448318Z", - "iopub.status.idle": "2024-08-12T18:54:04.456608Z", - "shell.execute_reply": "2024-08-12T18:54:04.455832Z" + "iopub.execute_input": "2024-08-15T19:27:52.946310Z", + "iopub.status.busy": "2024-08-15T19:27:52.945599Z", + "iopub.status.idle": "2024-08-15T19:27:52.953757Z", + "shell.execute_reply": "2024-08-15T19:27:52.953201Z" } }, "outputs": [ @@ -774,10 +774,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:04.458815Z", - "iopub.status.busy": "2024-08-12T18:54:04.458476Z", - "iopub.status.idle": "2024-08-12T18:54:04.462554Z", - "shell.execute_reply": "2024-08-12T18:54:04.462062Z" + "iopub.execute_input": "2024-08-15T19:27:52.956161Z", + "iopub.status.busy": "2024-08-15T19:27:52.955782Z", + "iopub.status.idle": "2024-08-15T19:27:52.959772Z", + "shell.execute_reply": "2024-08-15T19:27:52.959213Z" } }, "outputs": [], @@ -791,10 +791,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:04.464756Z", - "iopub.status.busy": "2024-08-12T18:54:04.464321Z", - "iopub.status.idle": "2024-08-12T18:54:04.467750Z", - "shell.execute_reply": "2024-08-12T18:54:04.467293Z" + "iopub.execute_input": "2024-08-15T19:27:52.961719Z", + "iopub.status.busy": "2024-08-15T19:27:52.961422Z", + "iopub.status.idle": "2024-08-15T19:27:52.964455Z", + "shell.execute_reply": "2024-08-15T19:27:52.963932Z" } }, "outputs": [ @@ -829,10 +829,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:04.469960Z", - "iopub.status.busy": "2024-08-12T18:54:04.469551Z", - "iopub.status.idle": "2024-08-12T18:54:04.472540Z", - "shell.execute_reply": "2024-08-12T18:54:04.472051Z" + "iopub.execute_input": "2024-08-15T19:27:52.966586Z", + "iopub.status.busy": "2024-08-15T19:27:52.966179Z", + "iopub.status.idle": "2024-08-15T19:27:52.969368Z", + "shell.execute_reply": "2024-08-15T19:27:52.968804Z" } }, "outputs": [], @@ -852,10 +852,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:04.474585Z", - "iopub.status.busy": "2024-08-12T18:54:04.474184Z", - "iopub.status.idle": "2024-08-12T18:54:04.481135Z", - "shell.execute_reply": "2024-08-12T18:54:04.480676Z" + "iopub.execute_input": "2024-08-15T19:27:52.971503Z", + "iopub.status.busy": "2024-08-15T19:27:52.971191Z", + "iopub.status.idle": "2024-08-15T19:27:52.978128Z", + "shell.execute_reply": "2024-08-15T19:27:52.977586Z" } }, "outputs": [ @@ -980,10 +980,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:04.483285Z", - "iopub.status.busy": "2024-08-12T18:54:04.482950Z", - "iopub.status.idle": "2024-08-12T18:54:04.708333Z", - "shell.execute_reply": "2024-08-12T18:54:04.707743Z" + "iopub.execute_input": "2024-08-15T19:27:52.980349Z", + "iopub.status.busy": "2024-08-15T19:27:52.979987Z", + "iopub.status.idle": "2024-08-15T19:27:53.206595Z", + "shell.execute_reply": "2024-08-15T19:27:53.206045Z" }, "scrolled": true }, @@ -1022,10 +1022,10 @@ "execution_count": 19, "metadata": { "execution": { - 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"if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -131,10 +131,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:15.660155Z", - "iopub.status.busy": "2024-08-12T18:54:15.659633Z", - "iopub.status.idle": "2024-08-12T18:54:15.662867Z", - "shell.execute_reply": "2024-08-12T18:54:15.662385Z" + "iopub.execute_input": "2024-08-15T19:28:02.361992Z", + "iopub.status.busy": "2024-08-15T19:28:02.361440Z", + "iopub.status.idle": "2024-08-15T19:28:02.364744Z", + "shell.execute_reply": "2024-08-15T19:28:02.364216Z" }, "id": "LaEiwXUiVHCS" }, @@ -157,10 +157,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:15.664832Z", - "iopub.status.busy": "2024-08-12T18:54:15.664650Z", - "iopub.status.idle": "2024-08-12T18:54:15.669779Z", - "shell.execute_reply": "2024-08-12T18:54:15.669342Z" + "iopub.execute_input": "2024-08-15T19:28:02.366877Z", + "iopub.status.busy": "2024-08-15T19:28:02.366431Z", + "iopub.status.idle": "2024-08-15T19:28:02.371038Z", + "shell.execute_reply": "2024-08-15T19:28:02.370461Z" }, "nbsphinx": "hidden" }, @@ -208,10 +208,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:15.671738Z", - "iopub.status.busy": "2024-08-12T18:54:15.671562Z", - "iopub.status.idle": "2024-08-12T18:54:17.893524Z", - "shell.execute_reply": "2024-08-12T18:54:17.892681Z" + "iopub.execute_input": "2024-08-15T19:28:02.373193Z", + "iopub.status.busy": "2024-08-15T19:28:02.372896Z", + "iopub.status.idle": "2024-08-15T19:28:04.255968Z", + "shell.execute_reply": "2024-08-15T19:28:04.255122Z" }, "id": "GRDPEg7-VOQe", "outputId": "cb886220-e86e-4a77-9f3a-d7844c37c3a6" @@ -242,10 +242,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:17.896656Z", - "iopub.status.busy": "2024-08-12T18:54:17.896108Z", - "iopub.status.idle": "2024-08-12T18:54:17.907522Z", - "shell.execute_reply": "2024-08-12T18:54:17.907061Z" + "iopub.execute_input": "2024-08-15T19:28:04.258975Z", + "iopub.status.busy": "2024-08-15T19:28:04.258542Z", + "iopub.status.idle": "2024-08-15T19:28:04.269974Z", + "shell.execute_reply": "2024-08-15T19:28:04.269415Z" }, "id": "FDA5sGZwUSur", "outputId": "0cedc509-63fd-4dc3-d32f-4b537dfe3895" @@ -329,10 +329,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:17.909690Z", - "iopub.status.busy": "2024-08-12T18:54:17.909399Z", - "iopub.status.idle": "2024-08-12T18:54:17.915243Z", - "shell.execute_reply": "2024-08-12T18:54:17.914767Z" + "iopub.execute_input": "2024-08-15T19:28:04.272212Z", + "iopub.status.busy": "2024-08-15T19:28:04.271858Z", + "iopub.status.idle": "2024-08-15T19:28:04.277516Z", + "shell.execute_reply": "2024-08-15T19:28:04.277042Z" }, "nbsphinx": "hidden" }, @@ -380,10 +380,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:17.917203Z", - "iopub.status.busy": "2024-08-12T18:54:17.917022Z", - "iopub.status.idle": "2024-08-12T18:54:18.401760Z", - "shell.execute_reply": "2024-08-12T18:54:18.401217Z" + "iopub.execute_input": "2024-08-15T19:28:04.279385Z", + "iopub.status.busy": "2024-08-15T19:28:04.279211Z", + "iopub.status.idle": "2024-08-15T19:28:04.717999Z", + "shell.execute_reply": "2024-08-15T19:28:04.717421Z" }, "id": "dLBvUZLlII5w", "outputId": "c6a4917f-4a82-4a89-9193-415072e45550" @@ -435,10 +435,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:18.403866Z", - "iopub.status.busy": "2024-08-12T18:54:18.403673Z", - "iopub.status.idle": "2024-08-12T18:54:19.860815Z", - "shell.execute_reply": "2024-08-12T18:54:19.860160Z" + "iopub.execute_input": "2024-08-15T19:28:04.720477Z", + "iopub.status.busy": "2024-08-15T19:28:04.719986Z", + "iopub.status.idle": "2024-08-15T19:28:05.547658Z", + "shell.execute_reply": "2024-08-15T19:28:05.547111Z" }, "id": "vL9lkiKsHvKr" }, @@ -474,10 +474,10 @@ "height": 143 }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:19.863289Z", - "iopub.status.busy": "2024-08-12T18:54:19.863103Z", - "iopub.status.idle": "2024-08-12T18:54:19.881662Z", - "shell.execute_reply": "2024-08-12T18:54:19.881178Z" + "iopub.execute_input": "2024-08-15T19:28:05.550114Z", + "iopub.status.busy": "2024-08-15T19:28:05.549770Z", + "iopub.status.idle": "2024-08-15T19:28:05.567955Z", + "shell.execute_reply": "2024-08-15T19:28:05.567477Z" }, "id": "obQYDKdLiUU6", "outputId": "4e923d5c-2cf4-4a5c-827b-0a4fea9d87e4" @@ -557,10 +557,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:19.883637Z", - "iopub.status.busy": "2024-08-12T18:54:19.883457Z", - "iopub.status.idle": "2024-08-12T18:54:19.886532Z", - "shell.execute_reply": "2024-08-12T18:54:19.886084Z" + "iopub.execute_input": "2024-08-15T19:28:05.569930Z", + "iopub.status.busy": "2024-08-15T19:28:05.569612Z", + "iopub.status.idle": "2024-08-15T19:28:05.572741Z", + "shell.execute_reply": "2024-08-15T19:28:05.572262Z" }, "id": "I8JqhOZgi94g" }, @@ -582,10 +582,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:19.888530Z", - "iopub.status.busy": "2024-08-12T18:54:19.888180Z", - "iopub.status.idle": "2024-08-12T18:54:34.498733Z", - "shell.execute_reply": "2024-08-12T18:54:34.498075Z" + "iopub.execute_input": "2024-08-15T19:28:05.574618Z", + "iopub.status.busy": "2024-08-15T19:28:05.574442Z", + "iopub.status.idle": "2024-08-15T19:28:19.351516Z", + "shell.execute_reply": "2024-08-15T19:28:19.350891Z" }, "id": "2FSQ2GR9R_YA" }, @@ -617,10 +617,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:34.501588Z", - "iopub.status.busy": "2024-08-12T18:54:34.501212Z", - "iopub.status.idle": "2024-08-12T18:54:34.505069Z", - "shell.execute_reply": "2024-08-12T18:54:34.504545Z" + "iopub.execute_input": "2024-08-15T19:28:19.354496Z", + "iopub.status.busy": "2024-08-15T19:28:19.354033Z", + "iopub.status.idle": "2024-08-15T19:28:19.357991Z", + "shell.execute_reply": "2024-08-15T19:28:19.357501Z" }, "id": "kAkY31IVXyr8", "outputId": "fd70d8d6-2f11-48d5-ae9c-a8c97d453632" @@ -680,10 +680,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:34.507196Z", - "iopub.status.busy": "2024-08-12T18:54:34.506852Z", - "iopub.status.idle": "2024-08-12T18:54:35.241502Z", - "shell.execute_reply": "2024-08-12T18:54:35.240901Z" + "iopub.execute_input": "2024-08-15T19:28:19.360150Z", + "iopub.status.busy": "2024-08-15T19:28:19.359816Z", + "iopub.status.idle": "2024-08-15T19:28:20.080726Z", + "shell.execute_reply": "2024-08-15T19:28:20.080116Z" }, "id": "i_drkY9YOcw4" }, @@ -717,10 +717,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.245317Z", - "iopub.status.busy": "2024-08-12T18:54:35.244326Z", - "iopub.status.idle": "2024-08-12T18:54:35.251232Z", - "shell.execute_reply": "2024-08-12T18:54:35.250716Z" + "iopub.execute_input": "2024-08-15T19:28:20.083716Z", + "iopub.status.busy": "2024-08-15T19:28:20.083264Z", + "iopub.status.idle": "2024-08-15T19:28:20.088269Z", + "shell.execute_reply": "2024-08-15T19:28:20.087684Z" }, "id": "_b-AQeoXOc7q", "outputId": "15ae534a-f517-4906-b177-ca91931a8954" @@ -767,10 +767,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.254892Z", - "iopub.status.busy": "2024-08-12T18:54:35.253950Z", - "iopub.status.idle": "2024-08-12T18:54:35.371220Z", - "shell.execute_reply": "2024-08-12T18:54:35.370579Z" + "iopub.execute_input": "2024-08-15T19:28:20.090852Z", + "iopub.status.busy": "2024-08-15T19:28:20.090343Z", + "iopub.status.idle": "2024-08-15T19:28:20.210836Z", + "shell.execute_reply": "2024-08-15T19:28:20.210257Z" } }, "outputs": [ @@ -807,10 +807,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.373827Z", - "iopub.status.busy": "2024-08-12T18:54:35.373627Z", - "iopub.status.idle": "2024-08-12T18:54:35.386543Z", - "shell.execute_reply": "2024-08-12T18:54:35.386056Z" + "iopub.execute_input": "2024-08-15T19:28:20.213328Z", + "iopub.status.busy": "2024-08-15T19:28:20.212901Z", + "iopub.status.idle": "2024-08-15T19:28:20.225740Z", + "shell.execute_reply": "2024-08-15T19:28:20.225286Z" }, "scrolled": true }, @@ -870,10 +870,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.388685Z", - "iopub.status.busy": "2024-08-12T18:54:35.388421Z", - "iopub.status.idle": "2024-08-12T18:54:35.396287Z", - "shell.execute_reply": "2024-08-12T18:54:35.395747Z" + "iopub.execute_input": "2024-08-15T19:28:20.227956Z", + "iopub.status.busy": "2024-08-15T19:28:20.227616Z", + "iopub.status.idle": "2024-08-15T19:28:20.235719Z", + "shell.execute_reply": "2024-08-15T19:28:20.235239Z" } }, "outputs": [ @@ -977,10 +977,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.398352Z", - "iopub.status.busy": "2024-08-12T18:54:35.398175Z", - "iopub.status.idle": "2024-08-12T18:54:35.402421Z", - "shell.execute_reply": "2024-08-12T18:54:35.401981Z" + "iopub.execute_input": "2024-08-15T19:28:20.237779Z", + "iopub.status.busy": "2024-08-15T19:28:20.237441Z", + "iopub.status.idle": "2024-08-15T19:28:20.241592Z", + "shell.execute_reply": "2024-08-15T19:28:20.241124Z" } }, "outputs": [ @@ -1018,10 +1018,10 @@ "height": 237 }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.404458Z", - "iopub.status.busy": "2024-08-12T18:54:35.404104Z", - "iopub.status.idle": "2024-08-12T18:54:35.409696Z", - "shell.execute_reply": "2024-08-12T18:54:35.409125Z" + "iopub.execute_input": "2024-08-15T19:28:20.243713Z", + "iopub.status.busy": "2024-08-15T19:28:20.243377Z", + "iopub.status.idle": "2024-08-15T19:28:20.248908Z", + "shell.execute_reply": "2024-08-15T19:28:20.248378Z" }, "id": "FQwRHgbclpsO", "outputId": "fee5c335-c00e-4fcc-f22b-718705e93182" @@ -1148,10 +1148,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.411873Z", - "iopub.status.busy": "2024-08-12T18:54:35.411459Z", - "iopub.status.idle": "2024-08-12T18:54:35.523406Z", - "shell.execute_reply": "2024-08-12T18:54:35.522815Z" + "iopub.execute_input": "2024-08-15T19:28:20.251049Z", + "iopub.status.busy": "2024-08-15T19:28:20.250697Z", + "iopub.status.idle": "2024-08-15T19:28:20.363458Z", + "shell.execute_reply": "2024-08-15T19:28:20.362991Z" }, "id": "ff1NFVlDoysO", "outputId": "8141a036-44c1-4349-c338-880432513e37" @@ -1205,10 +1205,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.525613Z", - "iopub.status.busy": "2024-08-12T18:54:35.525277Z", - "iopub.status.idle": "2024-08-12T18:54:35.630701Z", - "shell.execute_reply": "2024-08-12T18:54:35.630133Z" + "iopub.execute_input": "2024-08-15T19:28:20.365628Z", + "iopub.status.busy": "2024-08-15T19:28:20.365349Z", + "iopub.status.idle": "2024-08-15T19:28:20.468344Z", + "shell.execute_reply": "2024-08-15T19:28:20.467858Z" }, "id": "GZgovGkdiaiP", "outputId": "d76b2ccf-8be2-4f3a-df4c-2c5c99150db7" @@ -1253,10 +1253,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.632969Z", - "iopub.status.busy": "2024-08-12T18:54:35.632608Z", - "iopub.status.idle": "2024-08-12T18:54:35.735760Z", - "shell.execute_reply": "2024-08-12T18:54:35.735250Z" + "iopub.execute_input": "2024-08-15T19:28:20.470535Z", + "iopub.status.busy": "2024-08-15T19:28:20.470195Z", + "iopub.status.idle": "2024-08-15T19:28:20.569954Z", + "shell.execute_reply": "2024-08-15T19:28:20.569512Z" }, "id": "lfa2eHbMwG8R", "outputId": "6627ebe2-d439-4bf5-e2cb-44f6278ae86c" @@ -1297,10 +1297,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.738090Z", - "iopub.status.busy": "2024-08-12T18:54:35.737656Z", - "iopub.status.idle": "2024-08-12T18:54:35.841118Z", - "shell.execute_reply": "2024-08-12T18:54:35.840529Z" + "iopub.execute_input": "2024-08-15T19:28:20.572095Z", + "iopub.status.busy": "2024-08-15T19:28:20.571825Z", + "iopub.status.idle": "2024-08-15T19:28:20.674749Z", + "shell.execute_reply": "2024-08-15T19:28:20.674200Z" } }, "outputs": [ @@ -1348,10 +1348,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:35.843257Z", - "iopub.status.busy": "2024-08-12T18:54:35.843073Z", - "iopub.status.idle": "2024-08-12T18:54:35.846791Z", - "shell.execute_reply": 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"version_major": 2, "version_minor": 0} diff --git a/master/tutorials/datalab/datalab_advanced.ipynb b/master/tutorials/datalab/datalab_advanced.ipynb index 175c480da..9190aad9b 100644 --- a/master/tutorials/datalab/datalab_advanced.ipynb +++ b/master/tutorials/datalab/datalab_advanced.ipynb @@ -80,10 +80,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:41.056251Z", - "iopub.status.busy": "2024-08-12T18:54:41.056072Z", - "iopub.status.idle": "2024-08-12T18:54:42.472255Z", - "shell.execute_reply": "2024-08-12T18:54:42.471637Z" + "iopub.execute_input": "2024-08-15T19:28:24.865330Z", + "iopub.status.busy": "2024-08-15T19:28:24.864975Z", + "iopub.status.idle": "2024-08-15T19:28:26.252774Z", + "shell.execute_reply": "2024-08-15T19:28:26.252216Z" }, "nbsphinx": "hidden" }, @@ -93,7 +93,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"] # TODO: make sure this list is updated\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -118,10 +118,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:42.474736Z", - "iopub.status.busy": "2024-08-12T18:54:42.474444Z", - "iopub.status.idle": "2024-08-12T18:54:42.477548Z", - "shell.execute_reply": "2024-08-12T18:54:42.477075Z" + "iopub.execute_input": "2024-08-15T19:28:26.255353Z", + "iopub.status.busy": "2024-08-15T19:28:26.254870Z", + "iopub.status.idle": "2024-08-15T19:28:26.257822Z", + "shell.execute_reply": "2024-08-15T19:28:26.257367Z" } }, "outputs": [], @@ -252,10 +252,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:42.479701Z", - "iopub.status.busy": "2024-08-12T18:54:42.479369Z", - "iopub.status.idle": "2024-08-12T18:54:42.487756Z", - "shell.execute_reply": "2024-08-12T18:54:42.487291Z" + "iopub.execute_input": "2024-08-15T19:28:26.260094Z", + "iopub.status.busy": "2024-08-15T19:28:26.259738Z", + "iopub.status.idle": "2024-08-15T19:28:26.268148Z", + "shell.execute_reply": "2024-08-15T19:28:26.267709Z" }, "nbsphinx": "hidden" }, @@ -353,10 +353,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:42.489795Z", - "iopub.status.busy": "2024-08-12T18:54:42.489482Z", - "iopub.status.idle": "2024-08-12T18:54:42.494587Z", - "shell.execute_reply": "2024-08-12T18:54:42.494140Z" + "iopub.execute_input": "2024-08-15T19:28:26.270149Z", + "iopub.status.busy": "2024-08-15T19:28:26.269814Z", + "iopub.status.idle": "2024-08-15T19:28:26.274713Z", + "shell.execute_reply": "2024-08-15T19:28:26.274284Z" } }, "outputs": [], @@ -445,10 +445,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:42.496778Z", - "iopub.status.busy": "2024-08-12T18:54:42.496435Z", - "iopub.status.idle": "2024-08-12T18:54:42.504078Z", - "shell.execute_reply": "2024-08-12T18:54:42.503573Z" + "iopub.execute_input": "2024-08-15T19:28:26.276904Z", + "iopub.status.busy": "2024-08-15T19:28:26.276575Z", + "iopub.status.idle": "2024-08-15T19:28:26.284425Z", + "shell.execute_reply": "2024-08-15T19:28:26.283988Z" }, "nbsphinx": "hidden" }, @@ -517,10 +517,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:42.506139Z", - "iopub.status.busy": "2024-08-12T18:54:42.505804Z", - "iopub.status.idle": "2024-08-12T18:54:42.830541Z", - "shell.execute_reply": "2024-08-12T18:54:42.829968Z" + "iopub.execute_input": "2024-08-15T19:28:26.286480Z", + "iopub.status.busy": "2024-08-15T19:28:26.286036Z", + "iopub.status.idle": "2024-08-15T19:28:26.657555Z", + "shell.execute_reply": 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"model_name": "HTMLModel", @@ -1799,9 +1799,9 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_9d9eac6aa2924c35b65ba9e37e8f5ba6", + "layout": "IPY_MODEL_a6f59904b7df49a995a168365681347b", "placeholder": "​", - "style": "IPY_MODEL_53ad7637ce9042aeac54dad41f926eab", + "style": "IPY_MODEL_db5fdd4ed934443ab656f3c14121c7b0", "tabbable": null, "tooltip": null, "value": "Saving the dataset (1/1 shards): 100%" diff --git a/master/tutorials/datalab/datalab_quickstart.html b/master/tutorials/datalab/datalab_quickstart.html index d00b92717..96fdfda7f 100644 --- a/master/tutorials/datalab/datalab_quickstart.html +++ b/master/tutorials/datalab/datalab_quickstart.html @@ -1134,7 +1134,7 @@

    5. Learn more about the issues in your dataset\n", " 6\n", " underperforming_group\n", - " 0.901562\n", + " 0.926818\n", " 0\n", " \n", " \n", @@ -909,7 +909,7 @@ "3 near_duplicate 0.616034 4\n", "4 non_iid 0.821750 0\n", "5 class_imbalance 0.022727 3\n", - "6 underperforming_group 0.901562 0" + "6 underperforming_group 0.926818 0" ] }, "execution_count": 11, @@ -935,10 +935,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:52.193149Z", - "iopub.status.busy": "2024-08-12T18:54:52.192969Z", - "iopub.status.idle": "2024-08-12T18:54:52.198891Z", - "shell.execute_reply": "2024-08-12T18:54:52.198307Z" + "iopub.execute_input": "2024-08-15T19:28:35.528353Z", + "iopub.status.busy": "2024-08-15T19:28:35.528017Z", + "iopub.status.idle": "2024-08-15T19:28:35.533582Z", + "shell.execute_reply": "2024-08-15T19:28:35.533032Z" } }, "outputs": [ @@ -1005,10 +1005,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:52.200895Z", - "iopub.status.busy": "2024-08-12T18:54:52.200588Z", - "iopub.status.idle": "2024-08-12T18:54:52.211009Z", - "shell.execute_reply": "2024-08-12T18:54:52.210546Z" + "iopub.execute_input": "2024-08-15T19:28:35.535555Z", + "iopub.status.busy": "2024-08-15T19:28:35.535248Z", + "iopub.status.idle": "2024-08-15T19:28:35.545314Z", + "shell.execute_reply": "2024-08-15T19:28:35.544777Z" } }, "outputs": [ @@ -1065,7 +1065,7 @@ " False\n", " 1.0\n", " False\n", - " 1.0\n", + " 1.000000\n", " \n", " \n", " 1\n", @@ -1082,7 +1082,7 @@ " False\n", " 1.0\n", " False\n", - " 1.0\n", + " 0.910232\n", " \n", " \n", " 2\n", @@ -1099,7 +1099,7 @@ " False\n", " 1.0\n", " False\n", - " 1.0\n", + " 0.910232\n", " \n", " \n", " 3\n", @@ -1116,7 +1116,7 @@ " False\n", " 1.0\n", " False\n", - " 1.0\n", + " 0.890169\n", " \n", " \n", " 4\n", @@ -1133,7 +1133,7 @@ " False\n", " 1.0\n", " False\n", - " 1.0\n", + " 1.000000\n", " \n", " \n", "\n", @@ -1169,11 +1169,11 @@ "4 1.0 False \n", "\n", " underperforming_group_score \n", - "0 1.0 \n", - "1 1.0 \n", - "2 1.0 \n", - "3 1.0 \n", - "4 1.0 " + "0 1.000000 \n", + "1 0.910232 \n", + "2 0.910232 \n", + "3 0.890169 \n", + "4 1.000000 " ] }, "execution_count": 13, @@ -1200,10 +1200,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:52.213158Z", - "iopub.status.busy": "2024-08-12T18:54:52.212840Z", - "iopub.status.idle": "2024-08-12T18:54:52.221951Z", - "shell.execute_reply": "2024-08-12T18:54:52.221377Z" + "iopub.execute_input": "2024-08-15T19:28:35.547399Z", + "iopub.status.busy": "2024-08-15T19:28:35.547066Z", + "iopub.status.idle": "2024-08-15T19:28:35.555526Z", + "shell.execute_reply": "2024-08-15T19:28:35.555046Z" } }, "outputs": [ @@ -1319,10 +1319,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:52.224128Z", - "iopub.status.busy": "2024-08-12T18:54:52.223855Z", - "iopub.status.idle": "2024-08-12T18:54:52.230669Z", - "shell.execute_reply": "2024-08-12T18:54:52.230101Z" + "iopub.execute_input": "2024-08-15T19:28:35.557574Z", + "iopub.status.busy": "2024-08-15T19:28:35.557301Z", + "iopub.status.idle": "2024-08-15T19:28:35.564027Z", + "shell.execute_reply": "2024-08-15T19:28:35.563510Z" }, "scrolled": true }, @@ -1447,10 +1447,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:52.232850Z", - "iopub.status.busy": "2024-08-12T18:54:52.232463Z", - "iopub.status.idle": "2024-08-12T18:54:52.241829Z", - "shell.execute_reply": "2024-08-12T18:54:52.241257Z" + "iopub.execute_input": "2024-08-15T19:28:35.566026Z", + "iopub.status.busy": "2024-08-15T19:28:35.565847Z", + "iopub.status.idle": "2024-08-15T19:28:35.575518Z", + "shell.execute_reply": "2024-08-15T19:28:35.574981Z" } }, "outputs": [ @@ -1553,10 +1553,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:52.243956Z", - "iopub.status.busy": "2024-08-12T18:54:52.243626Z", - "iopub.status.idle": "2024-08-12T18:54:52.259258Z", - "shell.execute_reply": "2024-08-12T18:54:52.258809Z" + "iopub.execute_input": "2024-08-15T19:28:35.577501Z", + "iopub.status.busy": "2024-08-15T19:28:35.577333Z", + "iopub.status.idle": "2024-08-15T19:28:35.593402Z", + "shell.execute_reply": "2024-08-15T19:28:35.592979Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/datalab/image.html b/master/tutorials/datalab/image.html index e0ac45805..fa5552985 100644 --- a/master/tutorials/datalab/image.html +++ b/master/tutorials/datalab/image.html @@ -727,31 +727,31 @@

    2. Fetch and normalize the Fashion-MNIST dataset

    -
    +
    -
    +
    -
    +
    -
    +
    -
    +
    [3]:
@@ -806,7 +806,7 @@ 
    2. Fetch and normalize the Fashion-MNIST dataset
    -
    +

    Convert the transformed dataset to a torch dataset. Torch datasets are more efficient with dataloading in practice.

    @@ -1055,8 +1055,8 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
     
 Training on fold: 1 ...
-epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 5.009
-epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.734
+epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 4.813
+epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.540
 Computing feature embeddings ...

    @@ -1064,7 +1064,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
    -
    +
    @@ -1078,7 +1078,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings

    -
    +
    @@ -1087,8 +1087,8 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
     
 Training on fold: 2 ...
-epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 5.225
-epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.711
+epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 4.906
+epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.579
 Computing feature embeddings ...

    @@ -1096,7 +1096,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
    -
    +
    @@ -1110,7 +1110,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings

    -
    +
    @@ -1119,8 +1119,8 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
     
 Training on fold: 3 ...
-epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 4.971
-epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.749
+epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 4.730
+epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.565
 Computing feature embeddings ...

    @@ -1128,7 +1128,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
    -
    +
    @@ -1142,7 +1142,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings

    -
    +
    @@ -1204,7 +1204,7 @@

    7. Use cleanlab to find issues

    -
    +
    @@ -1919,35 +1919,35 @@

    Dark images - dark_score is_dark_issue + dark_score 34848 - 0.203922 True + 0.203922 50270 - 0.204588 True + 0.204588 3936 - 0.213098 True + 0.213098 733 - 0.217686 True + 0.217686 8094 - 0.230118 True + 0.230118 @@ -2097,7 +2097,7 @@

    Easy ModeCleanlab Studio which will automatically produce one for you. Super easy to use, Cleanlab Studio is no-code platform for data-centric AI that automatically: detects data issues (more types of issues than this cleanlab package), helps you quickly correct these data issues, confidently labels large subsets of an unlabeled dataset, and provides other smart metadata about each of your data points – all powered by a system that automatically trains/deploys the best ML model for your data. Try it for free!

    diff --git a/master/tutorials/datalab/image.ipynb b/master/tutorials/datalab/image.ipynb index 255960716..e82b22811 100644 --- a/master/tutorials/datalab/image.ipynb +++ b/master/tutorials/datalab/image.ipynb @@ -71,10 +71,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:55.167990Z", - "iopub.status.busy": "2024-08-12T18:54:55.167498Z", - "iopub.status.idle": "2024-08-12T18:54:58.200814Z", - "shell.execute_reply": "2024-08-12T18:54:58.200214Z" + "iopub.execute_input": "2024-08-15T19:28:38.248143Z", + "iopub.status.busy": "2024-08-15T19:28:38.247971Z", + "iopub.status.idle": "2024-08-15T19:28:41.190910Z", + "shell.execute_reply": "2024-08-15T19:28:41.190239Z" }, "nbsphinx": "hidden" }, @@ -112,10 +112,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:58.203267Z", - "iopub.status.busy": "2024-08-12T18:54:58.202968Z", - "iopub.status.idle": "2024-08-12T18:54:58.206608Z", - "shell.execute_reply": "2024-08-12T18:54:58.206150Z" + "iopub.execute_input": "2024-08-15T19:28:41.193639Z", + "iopub.status.busy": "2024-08-15T19:28:41.193292Z", + "iopub.status.idle": "2024-08-15T19:28:41.197110Z", + "shell.execute_reply": "2024-08-15T19:28:41.196645Z" } }, "outputs": [], @@ -152,17 +152,17 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:54:58.208613Z", - "iopub.status.busy": "2024-08-12T18:54:58.208300Z", - "iopub.status.idle": "2024-08-12T18:55:03.426332Z", - "shell.execute_reply": "2024-08-12T18:55:03.425846Z" + "iopub.execute_input": "2024-08-15T19:28:41.199057Z", + "iopub.status.busy": "2024-08-15T19:28:41.198879Z", + "iopub.status.idle": "2024-08-15T19:28:44.013146Z", + "shell.execute_reply": "2024-08-15T19:28:44.012589Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5536055315cc48758ef861d7a11a8759", + "model_id": "aad0d6d230c3476281fffa76aaeb8a86", "version_major": 2, "version_minor": 0 }, @@ -176,7 +176,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "94289cd6e6de468db051fd838ba56323", + "model_id": "bfadf7bb6c884091b46cca6d7bd10362", "version_major": 2, "version_minor": 0 }, @@ -190,7 +190,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5530f4d814dc4873935b56a3bc07d13e", + "model_id": "fa273908c1d1415f807e8c16c9563328", "version_major": 2, "version_minor": 0 }, @@ -204,7 +204,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d7183df8c95b49f89720bff1674cd315", + "model_id": "a87f9cbbaa6945b59df6017587ac3e80", "version_major": 2, "version_minor": 0 }, @@ -218,7 +218,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e31ea71bbfe34e54bde0f8eba6e3e41b", + "model_id": "5bd2f6a19cfa45caa5bcf973b4fa5824", "version_major": 2, "version_minor": 0 }, @@ -260,10 +260,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:03.428583Z", - "iopub.status.busy": "2024-08-12T18:55:03.428213Z", - "iopub.status.idle": "2024-08-12T18:55:03.432037Z", - "shell.execute_reply": "2024-08-12T18:55:03.431490Z" + "iopub.execute_input": "2024-08-15T19:28:44.015432Z", + "iopub.status.busy": "2024-08-15T19:28:44.015149Z", + "iopub.status.idle": "2024-08-15T19:28:44.018967Z", + "shell.execute_reply": "2024-08-15T19:28:44.018422Z" } }, "outputs": [ @@ -288,17 +288,17 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:03.433996Z", - "iopub.status.busy": "2024-08-12T18:55:03.433690Z", - "iopub.status.idle": "2024-08-12T18:55:15.156554Z", - "shell.execute_reply": "2024-08-12T18:55:15.155860Z" + "iopub.execute_input": "2024-08-15T19:28:44.020907Z", + "iopub.status.busy": "2024-08-15T19:28:44.020644Z", + "iopub.status.idle": "2024-08-15T19:28:55.663076Z", + "shell.execute_reply": "2024-08-15T19:28:55.662510Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0e98a483d8634a7c9c26dc079f884fe5", + "model_id": "5d84638f6b0e44abb8f0e126007e3846", "version_major": 2, "version_minor": 0 }, @@ -336,10 +336,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:15.159276Z", - "iopub.status.busy": "2024-08-12T18:55:15.158914Z", - "iopub.status.idle": "2024-08-12T18:55:34.063937Z", - "shell.execute_reply": "2024-08-12T18:55:34.063396Z" + "iopub.execute_input": "2024-08-15T19:28:55.665690Z", + "iopub.status.busy": "2024-08-15T19:28:55.665342Z", + "iopub.status.idle": "2024-08-15T19:29:13.831286Z", + "shell.execute_reply": "2024-08-15T19:29:13.830608Z" } }, "outputs": [], @@ -372,10 +372,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:34.066694Z", - "iopub.status.busy": "2024-08-12T18:55:34.066291Z", - "iopub.status.idle": "2024-08-12T18:55:34.072237Z", - "shell.execute_reply": "2024-08-12T18:55:34.071765Z" + "iopub.execute_input": "2024-08-15T19:29:13.834154Z", + "iopub.status.busy": "2024-08-15T19:29:13.833810Z", + "iopub.status.idle": "2024-08-15T19:29:13.838676Z", + "shell.execute_reply": "2024-08-15T19:29:13.838144Z" } }, "outputs": [], @@ -413,10 +413,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:34.074339Z", - "iopub.status.busy": "2024-08-12T18:55:34.073991Z", - "iopub.status.idle": "2024-08-12T18:55:34.078224Z", - "shell.execute_reply": "2024-08-12T18:55:34.077811Z" + "iopub.execute_input": "2024-08-15T19:29:13.840801Z", + "iopub.status.busy": "2024-08-15T19:29:13.840408Z", + "iopub.status.idle": "2024-08-15T19:29:13.844547Z", + "shell.execute_reply": "2024-08-15T19:29:13.844013Z" }, "nbsphinx": "hidden" }, @@ -553,10 +553,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:34.080424Z", - "iopub.status.busy": "2024-08-12T18:55:34.080076Z", - "iopub.status.idle": "2024-08-12T18:55:34.089197Z", - "shell.execute_reply": "2024-08-12T18:55:34.088740Z" + "iopub.execute_input": "2024-08-15T19:29:13.846686Z", + "iopub.status.busy": "2024-08-15T19:29:13.846388Z", + "iopub.status.idle": "2024-08-15T19:29:13.855304Z", + "shell.execute_reply": "2024-08-15T19:29:13.854742Z" }, "nbsphinx": "hidden" }, @@ -681,10 +681,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:34.091312Z", - "iopub.status.busy": "2024-08-12T18:55:34.090965Z", - "iopub.status.idle": "2024-08-12T18:55:34.119087Z", - "shell.execute_reply": "2024-08-12T18:55:34.118609Z" + "iopub.execute_input": "2024-08-15T19:29:13.857458Z", + "iopub.status.busy": "2024-08-15T19:29:13.857145Z", + "iopub.status.idle": "2024-08-15T19:29:13.883926Z", + "shell.execute_reply": "2024-08-15T19:29:13.883349Z" } }, "outputs": [], @@ -721,10 +721,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:55:34.121415Z", - "iopub.status.busy": "2024-08-12T18:55:34.121048Z", - "iopub.status.idle": "2024-08-12T18:56:08.107752Z", - "shell.execute_reply": "2024-08-12T18:56:08.107079Z" + "iopub.execute_input": "2024-08-15T19:29:13.886198Z", + "iopub.status.busy": "2024-08-15T19:29:13.885860Z", + "iopub.status.idle": "2024-08-15T19:29:46.678339Z", + "shell.execute_reply": "2024-08-15T19:29:46.677742Z" } }, "outputs": [ @@ -740,21 +740,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 5.009\n" + "epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 4.813\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.734\n", + "epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.540\n", "Computing feature embeddings ...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6ee42831ebd04c1abdb02a45dd8b1c41", + "model_id": "e279996356a24deebea207d022fd1d5e", "version_major": 2, "version_minor": 0 }, @@ -775,7 +775,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1f9027ac4265465c93cb18dc1bd30292", + "model_id": "3de6fc3bd9854ce995e1fd55ec0833b9", "version_major": 2, "version_minor": 0 }, @@ -798,21 +798,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 5.225\n" + "epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 4.906\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.711\n", + "epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.579\n", "Computing feature embeddings ...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "092583d713a644899085990919e92801", + "model_id": "0c14c28ca7da4659bca98b0567100829", "version_major": 2, "version_minor": 0 }, @@ -833,7 +833,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "52340a16943f47a2bf680589345a1330", + "model_id": "8e816f1d1c4144d49509bc39b029e3b9", "version_major": 2, "version_minor": 0 }, @@ -856,21 +856,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 4.971\n" + "epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 4.730\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.749\n", + "epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.565\n", "Computing feature embeddings ...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4f89d806ff8c4eb8979271cf81ddabb4", + "model_id": "34987bd0e89c441f960165e5191fd3af", "version_major": 2, "version_minor": 0 }, @@ -891,7 +891,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1788966d26a6427ca2e657ccbccc5011", + "model_id": "12a8d998f6b448a38a6fd776c62a4354", "version_major": 2, "version_minor": 0 }, @@ -970,10 +970,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:56:08.110568Z", - "iopub.status.busy": "2024-08-12T18:56:08.110135Z", - "iopub.status.idle": "2024-08-12T18:56:08.128279Z", - "shell.execute_reply": "2024-08-12T18:56:08.127694Z" + "iopub.execute_input": "2024-08-15T19:29:46.681020Z", + "iopub.status.busy": "2024-08-15T19:29:46.680601Z", + "iopub.status.idle": "2024-08-15T19:29:46.697530Z", + "shell.execute_reply": "2024-08-15T19:29:46.697037Z" } }, "outputs": [], @@ -998,10 +998,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:56:08.130938Z", - "iopub.status.busy": "2024-08-12T18:56:08.130451Z", - "iopub.status.idle": "2024-08-12T18:56:08.620894Z", - "shell.execute_reply": "2024-08-12T18:56:08.620328Z" + "iopub.execute_input": "2024-08-15T19:29:46.699814Z", + "iopub.status.busy": "2024-08-15T19:29:46.699447Z", + "iopub.status.idle": "2024-08-15T19:29:47.160250Z", + "shell.execute_reply": "2024-08-15T19:29:47.159697Z" } }, "outputs": [], @@ -1021,10 +1021,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:56:08.623509Z", - "iopub.status.busy": "2024-08-12T18:56:08.623124Z", - "iopub.status.idle": "2024-08-12T18:58:01.771753Z", - "shell.execute_reply": "2024-08-12T18:58:01.771037Z" + "iopub.execute_input": "2024-08-15T19:29:47.162748Z", + "iopub.status.busy": "2024-08-15T19:29:47.162389Z", + "iopub.status.idle": "2024-08-15T19:31:37.365010Z", + "shell.execute_reply": "2024-08-15T19:31:37.364325Z" } }, "outputs": [ @@ -1063,7 +1063,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a781e7b0a1eb4996a753d8f47a0d6cd0", + "model_id": "d0301a352bcd48278129fd4b79c1849b", "version_major": 2, "version_minor": 0 }, @@ -1108,10 +1108,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:01.774355Z", - "iopub.status.busy": "2024-08-12T18:58:01.773772Z", - "iopub.status.idle": "2024-08-12T18:58:02.253989Z", - "shell.execute_reply": "2024-08-12T18:58:02.253342Z" + "iopub.execute_input": "2024-08-15T19:31:37.367625Z", + "iopub.status.busy": "2024-08-15T19:31:37.367250Z", + "iopub.status.idle": "2024-08-15T19:31:37.819935Z", + "shell.execute_reply": "2024-08-15T19:31:37.819319Z" } }, "outputs": [ @@ -1257,10 +1257,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:02.256482Z", - "iopub.status.busy": "2024-08-12T18:58:02.256118Z", - "iopub.status.idle": "2024-08-12T18:58:02.318086Z", - "shell.execute_reply": "2024-08-12T18:58:02.317530Z" + "iopub.execute_input": "2024-08-15T19:31:37.822900Z", + "iopub.status.busy": "2024-08-15T19:31:37.822418Z", + "iopub.status.idle": "2024-08-15T19:31:37.884525Z", + "shell.execute_reply": "2024-08-15T19:31:37.884026Z" } }, "outputs": [ @@ -1364,10 +1364,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:02.320656Z", - "iopub.status.busy": "2024-08-12T18:58:02.320122Z", - "iopub.status.idle": "2024-08-12T18:58:02.329554Z", - "shell.execute_reply": "2024-08-12T18:58:02.329055Z" + "iopub.execute_input": "2024-08-15T19:31:37.886714Z", + "iopub.status.busy": "2024-08-15T19:31:37.886369Z", + "iopub.status.idle": "2024-08-15T19:31:37.894651Z", + "shell.execute_reply": "2024-08-15T19:31:37.894231Z" } }, "outputs": [ @@ -1497,10 +1497,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:02.331983Z", - "iopub.status.busy": "2024-08-12T18:58:02.331537Z", - "iopub.status.idle": "2024-08-12T18:58:02.336399Z", - "shell.execute_reply": "2024-08-12T18:58:02.335919Z" + "iopub.execute_input": "2024-08-15T19:31:37.896787Z", + "iopub.status.busy": "2024-08-15T19:31:37.896463Z", + "iopub.status.idle": "2024-08-15T19:31:37.900951Z", + "shell.execute_reply": "2024-08-15T19:31:37.900508Z" }, "nbsphinx": "hidden" }, @@ -1546,10 +1546,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:02.338459Z", - "iopub.status.busy": "2024-08-12T18:58:02.338116Z", - "iopub.status.idle": "2024-08-12T18:58:02.833078Z", - "shell.execute_reply": "2024-08-12T18:58:02.832432Z" + "iopub.execute_input": "2024-08-15T19:31:37.903002Z", + "iopub.status.busy": "2024-08-15T19:31:37.902663Z", + "iopub.status.idle": "2024-08-15T19:31:38.407084Z", + "shell.execute_reply": "2024-08-15T19:31:38.406456Z" } }, "outputs": [ @@ -1584,10 +1584,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:02.835684Z", - "iopub.status.busy": "2024-08-12T18:58:02.835299Z", - "iopub.status.idle": "2024-08-12T18:58:02.844200Z", - "shell.execute_reply": "2024-08-12T18:58:02.843719Z" + "iopub.execute_input": "2024-08-15T19:31:38.409178Z", + "iopub.status.busy": "2024-08-15T19:31:38.408999Z", + "iopub.status.idle": "2024-08-15T19:31:38.417344Z", + "shell.execute_reply": "2024-08-15T19:31:38.416780Z" } }, "outputs": [ @@ -1754,10 +1754,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:02.846427Z", - "iopub.status.busy": "2024-08-12T18:58:02.846066Z", - "iopub.status.idle": "2024-08-12T18:58:02.853397Z", - "shell.execute_reply": "2024-08-12T18:58:02.852926Z" + "iopub.execute_input": "2024-08-15T19:31:38.419449Z", + "iopub.status.busy": "2024-08-15T19:31:38.419145Z", + "iopub.status.idle": "2024-08-15T19:31:38.426440Z", + "shell.execute_reply": "2024-08-15T19:31:38.425969Z" }, "nbsphinx": "hidden" }, @@ -1833,10 +1833,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:02.855444Z", - "iopub.status.busy": "2024-08-12T18:58:02.855103Z", - "iopub.status.idle": "2024-08-12T18:58:03.646581Z", - "shell.execute_reply": "2024-08-12T18:58:03.645923Z" + "iopub.execute_input": "2024-08-15T19:31:38.428508Z", + "iopub.status.busy": "2024-08-15T19:31:38.428205Z", + "iopub.status.idle": "2024-08-15T19:31:39.174364Z", + "shell.execute_reply": "2024-08-15T19:31:39.173880Z" } }, "outputs": [ @@ -1873,10 +1873,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:03.649104Z", - "iopub.status.busy": "2024-08-12T18:58:03.648717Z", - "iopub.status.idle": "2024-08-12T18:58:03.665682Z", - "shell.execute_reply": "2024-08-12T18:58:03.665186Z" + "iopub.execute_input": "2024-08-15T19:31:39.176443Z", + "iopub.status.busy": "2024-08-15T19:31:39.176268Z", + "iopub.status.idle": "2024-08-15T19:31:39.191628Z", + "shell.execute_reply": "2024-08-15T19:31:39.191035Z" } }, "outputs": [ @@ -2033,10 +2033,10 @@ "execution_count": 24, "metadata": { "execution": { - 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"iopub.execute_input": "2024-08-12T18:58:04.074551Z", - "iopub.status.busy": "2024-08-12T18:58:04.073757Z", - "iopub.status.idle": "2024-08-12T18:58:04.083617Z", - "shell.execute_reply": "2024-08-12T18:58:04.083182Z" + "iopub.execute_input": "2024-08-15T19:31:39.670821Z", + "iopub.status.busy": "2024-08-15T19:31:39.670436Z", + "iopub.status.idle": "2024-08-15T19:31:39.679833Z", + "shell.execute_reply": "2024-08-15T19:31:39.679348Z" } }, "outputs": [ @@ -2194,47 +2194,47 @@ " \n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 34848\n", - " 0.203922\n", " True\n", + " 0.203922\n", " \n", " \n", " 50270\n", - " 0.204588\n", " True\n", + " 0.204588\n", " \n", " \n", " 3936\n", - " 0.213098\n", " True\n", + " 0.213098\n", " \n", " \n", " 733\n", - " 0.217686\n", " True\n", + " 0.217686\n", " \n", " \n", " 8094\n", - " 0.230118\n", " True\n", + " 0.230118\n", " \n", " \n", "\n", "

    " ], "text/plain": [ - " dark_score is_dark_issue\n", - "34848 0.203922 True\n", - "50270 0.204588 True\n", - "3936 0.213098 True\n", - "733 0.217686 True\n", - "8094 0.230118 True" + " is_dark_issue dark_score\n", + "34848 True 0.203922\n", + "50270 True 0.204588\n", + "3936 True 0.213098\n", + "733 True 0.217686\n", + "8094 True 0.230118" ] }, "execution_count": 26, @@ -2297,10 +2297,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:04.085975Z", - "iopub.status.busy": "2024-08-12T18:58:04.085795Z", - "iopub.status.idle": "2024-08-12T18:58:04.090563Z", - "shell.execute_reply": "2024-08-12T18:58:04.089872Z" + "iopub.execute_input": "2024-08-15T19:31:39.682244Z", + "iopub.status.busy": "2024-08-15T19:31:39.681876Z", + "iopub.status.idle": "2024-08-15T19:31:39.687591Z", + "shell.execute_reply": "2024-08-15T19:31:39.687095Z" }, "nbsphinx": "hidden" }, @@ -2337,10 +2337,10 @@ "execution_count": 28, "metadata": { "execution": { - 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"min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "f74157c274094c55a3fe2d8510370182": { + "fdc44c9b7d6e41209f597b3c9dbc7f81": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7515,33 +7541,7 @@ "width": null } }, - "f76fd1f88dbf476396c45b3dee352fb6": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_911d5b0e02934260a9bda52a7fa9fded", - "max": 40.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_7156eac180cd40748551472472a5e725", - "tabbable": null, - "tooltip": null, - "value": 40.0 - } - }, - "fab5e3871a7541b89cf8e8f2b9523a48": { + "fdf2f14ae93c4dc58e36eafe192f80f9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", diff --git a/master/tutorials/datalab/tabular.ipynb b/master/tutorials/datalab/tabular.ipynb index 7615eeea3..198584046 100644 --- a/master/tutorials/datalab/tabular.ipynb +++ b/master/tutorials/datalab/tabular.ipynb @@ -73,10 +73,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:08.421396Z", - "iopub.status.busy": "2024-08-12T18:58:08.421222Z", - "iopub.status.idle": "2024-08-12T18:58:09.859247Z", - "shell.execute_reply": "2024-08-12T18:58:09.858687Z" + "iopub.execute_input": "2024-08-15T19:31:43.610518Z", + "iopub.status.busy": "2024-08-15T19:31:43.610345Z", + "iopub.status.idle": "2024-08-15T19:31:45.001434Z", + "shell.execute_reply": "2024-08-15T19:31:45.000871Z" }, "nbsphinx": "hidden" }, @@ -86,7 +86,7 @@ "dependencies = [\"cleanlab\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -111,10 +111,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:09.861826Z", - "iopub.status.busy": "2024-08-12T18:58:09.861509Z", - "iopub.status.idle": "2024-08-12T18:58:09.881647Z", - "shell.execute_reply": "2024-08-12T18:58:09.881161Z" + "iopub.execute_input": "2024-08-15T19:31:45.004017Z", + "iopub.status.busy": "2024-08-15T19:31:45.003571Z", + "iopub.status.idle": "2024-08-15T19:31:45.022197Z", + "shell.execute_reply": "2024-08-15T19:31:45.021643Z" } }, "outputs": [], @@ -154,10 +154,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:09.884197Z", - "iopub.status.busy": "2024-08-12T18:58:09.883893Z", - "iopub.status.idle": "2024-08-12T18:58:09.930793Z", - "shell.execute_reply": "2024-08-12T18:58:09.930292Z" + "iopub.execute_input": "2024-08-15T19:31:45.024730Z", + "iopub.status.busy": "2024-08-15T19:31:45.024330Z", + "iopub.status.idle": "2024-08-15T19:31:45.049718Z", + "shell.execute_reply": "2024-08-15T19:31:45.049182Z" } }, "outputs": [ @@ -264,10 +264,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:09.933083Z", - "iopub.status.busy": "2024-08-12T18:58:09.932674Z", - "iopub.status.idle": "2024-08-12T18:58:09.936196Z", - "shell.execute_reply": "2024-08-12T18:58:09.935752Z" + "iopub.execute_input": "2024-08-15T19:31:45.051739Z", + "iopub.status.busy": "2024-08-15T19:31:45.051438Z", + "iopub.status.idle": "2024-08-15T19:31:45.054831Z", + "shell.execute_reply": "2024-08-15T19:31:45.054299Z" } }, "outputs": [], @@ -288,10 +288,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:09.938163Z", - "iopub.status.busy": "2024-08-12T18:58:09.937983Z", - "iopub.status.idle": "2024-08-12T18:58:09.945592Z", - "shell.execute_reply": "2024-08-12T18:58:09.945114Z" + "iopub.execute_input": "2024-08-15T19:31:45.056918Z", + "iopub.status.busy": "2024-08-15T19:31:45.056511Z", + "iopub.status.idle": "2024-08-15T19:31:45.063959Z", + "shell.execute_reply": "2024-08-15T19:31:45.063414Z" } }, "outputs": [], @@ -336,10 +336,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:09.947753Z", - "iopub.status.busy": "2024-08-12T18:58:09.947411Z", - "iopub.status.idle": "2024-08-12T18:58:09.950143Z", - "shell.execute_reply": "2024-08-12T18:58:09.949695Z" + "iopub.execute_input": "2024-08-15T19:31:45.066089Z", + "iopub.status.busy": "2024-08-15T19:31:45.065912Z", + "iopub.status.idle": "2024-08-15T19:31:45.068593Z", + "shell.execute_reply": "2024-08-15T19:31:45.068048Z" } }, "outputs": [], @@ -362,10 +362,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:09.951984Z", - "iopub.status.busy": "2024-08-12T18:58:09.951813Z", - "iopub.status.idle": "2024-08-12T18:58:13.120769Z", - "shell.execute_reply": "2024-08-12T18:58:13.120089Z" + "iopub.execute_input": "2024-08-15T19:31:45.070633Z", + "iopub.status.busy": "2024-08-15T19:31:45.070312Z", + "iopub.status.idle": "2024-08-15T19:31:48.169080Z", + "shell.execute_reply": "2024-08-15T19:31:48.168527Z" } }, "outputs": [], @@ -401,10 +401,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:13.123683Z", - "iopub.status.busy": "2024-08-12T18:58:13.123230Z", - "iopub.status.idle": "2024-08-12T18:58:13.133515Z", - "shell.execute_reply": "2024-08-12T18:58:13.133012Z" + "iopub.execute_input": "2024-08-15T19:31:48.171707Z", + "iopub.status.busy": "2024-08-15T19:31:48.171310Z", + "iopub.status.idle": "2024-08-15T19:31:48.181132Z", + "shell.execute_reply": "2024-08-15T19:31:48.180688Z" } }, "outputs": [], @@ -436,10 +436,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:13.135799Z", - "iopub.status.busy": "2024-08-12T18:58:13.135466Z", - "iopub.status.idle": "2024-08-12T18:58:15.356714Z", - "shell.execute_reply": "2024-08-12T18:58:15.355987Z" + "iopub.execute_input": "2024-08-15T19:31:48.183209Z", + "iopub.status.busy": "2024-08-15T19:31:48.182879Z", + "iopub.status.idle": "2024-08-15T19:31:50.284568Z", + "shell.execute_reply": "2024-08-15T19:31:50.283979Z" } }, "outputs": [ @@ -476,10 +476,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.359491Z", - "iopub.status.busy": "2024-08-12T18:58:15.358912Z", - "iopub.status.idle": "2024-08-12T18:58:15.378894Z", - "shell.execute_reply": "2024-08-12T18:58:15.378329Z" + "iopub.execute_input": "2024-08-15T19:31:50.287040Z", + "iopub.status.busy": "2024-08-15T19:31:50.286625Z", + "iopub.status.idle": "2024-08-15T19:31:50.305480Z", + "shell.execute_reply": "2024-08-15T19:31:50.305017Z" }, "scrolled": true }, @@ -609,10 +609,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.381408Z", - "iopub.status.busy": "2024-08-12T18:58:15.381025Z", - "iopub.status.idle": "2024-08-12T18:58:15.389610Z", - "shell.execute_reply": "2024-08-12T18:58:15.389010Z" + "iopub.execute_input": "2024-08-15T19:31:50.307596Z", + "iopub.status.busy": "2024-08-15T19:31:50.307260Z", + "iopub.status.idle": "2024-08-15T19:31:50.314962Z", + "shell.execute_reply": "2024-08-15T19:31:50.314451Z" } }, "outputs": [ @@ -716,10 +716,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.391998Z", - "iopub.status.busy": "2024-08-12T18:58:15.391635Z", - "iopub.status.idle": "2024-08-12T18:58:15.401546Z", - "shell.execute_reply": "2024-08-12T18:58:15.400962Z" + "iopub.execute_input": "2024-08-15T19:31:50.316919Z", + "iopub.status.busy": "2024-08-15T19:31:50.316609Z", + "iopub.status.idle": "2024-08-15T19:31:50.325724Z", + "shell.execute_reply": "2024-08-15T19:31:50.325161Z" } }, "outputs": [ @@ -848,10 +848,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.403711Z", - "iopub.status.busy": "2024-08-12T18:58:15.403525Z", - "iopub.status.idle": "2024-08-12T18:58:15.412500Z", - "shell.execute_reply": "2024-08-12T18:58:15.411891Z" + "iopub.execute_input": "2024-08-15T19:31:50.327823Z", + "iopub.status.busy": "2024-08-15T19:31:50.327427Z", + "iopub.status.idle": "2024-08-15T19:31:50.335069Z", + "shell.execute_reply": "2024-08-15T19:31:50.334607Z" } }, "outputs": [ @@ -965,10 +965,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.415177Z", - "iopub.status.busy": "2024-08-12T18:58:15.414739Z", - "iopub.status.idle": "2024-08-12T18:58:15.424092Z", - "shell.execute_reply": "2024-08-12T18:58:15.423595Z" + "iopub.execute_input": "2024-08-15T19:31:50.336997Z", + "iopub.status.busy": "2024-08-15T19:31:50.336823Z", + "iopub.status.idle": "2024-08-15T19:31:50.345688Z", + "shell.execute_reply": "2024-08-15T19:31:50.345229Z" } }, "outputs": [ @@ -1079,10 +1079,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.426173Z", - "iopub.status.busy": "2024-08-12T18:58:15.425991Z", - "iopub.status.idle": "2024-08-12T18:58:15.433609Z", - "shell.execute_reply": "2024-08-12T18:58:15.433049Z" + "iopub.execute_input": "2024-08-15T19:31:50.347811Z", + "iopub.status.busy": "2024-08-15T19:31:50.347482Z", + "iopub.status.idle": "2024-08-15T19:31:50.354794Z", + "shell.execute_reply": "2024-08-15T19:31:50.354246Z" } }, "outputs": [ @@ -1197,10 +1197,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.435695Z", - "iopub.status.busy": "2024-08-12T18:58:15.435412Z", - "iopub.status.idle": "2024-08-12T18:58:15.442825Z", - "shell.execute_reply": "2024-08-12T18:58:15.442358Z" + "iopub.execute_input": "2024-08-15T19:31:50.356892Z", + "iopub.status.busy": "2024-08-15T19:31:50.356619Z", + "iopub.status.idle": "2024-08-15T19:31:50.364182Z", + "shell.execute_reply": "2024-08-15T19:31:50.363733Z" } }, "outputs": [ @@ -1306,10 +1306,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:15.444907Z", - "iopub.status.busy": "2024-08-12T18:58:15.444586Z", - "iopub.status.idle": "2024-08-12T18:58:15.453151Z", - "shell.execute_reply": "2024-08-12T18:58:15.452574Z" + "iopub.execute_input": "2024-08-15T19:31:50.366316Z", + "iopub.status.busy": "2024-08-15T19:31:50.365980Z", + "iopub.status.idle": "2024-08-15T19:31:50.373820Z", + "shell.execute_reply": "2024-08-15T19:31:50.373370Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/datalab/text.html b/master/tutorials/datalab/text.html index 025272312..909c6edb9 100644 --- a/master/tutorials/datalab/text.html +++ b/master/tutorials/datalab/text.html @@ -791,7 +791,7 @@

    2. Load and format the text dataset 
     This dataset has 10 classes.
-Classes: {'card_about_to_expire', 'supported_cards_and_currencies', 'apple_pay_or_google_pay', 'change_pin', 'beneficiary_not_allowed', 'getting_spare_card', 'visa_or_mastercard', 'cancel_transfer', 'lost_or_stolen_phone', 'card_payment_fee_charged'}
+Classes: {'apple_pay_or_google_pay', 'cancel_transfer', 'card_about_to_expire', 'lost_or_stolen_phone', 'card_payment_fee_charged', 'change_pin', 'beneficiary_not_allowed', 'visa_or_mastercard', 'supported_cards_and_currencies', 'getting_spare_card'}

    Let’s view the i-th example in the dataset:

    diff --git a/master/tutorials/datalab/text.ipynb b/master/tutorials/datalab/text.ipynb index 277e568e0..642c596b2 100644 --- a/master/tutorials/datalab/text.ipynb +++ b/master/tutorials/datalab/text.ipynb @@ -75,10 +75,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:18.401024Z", - "iopub.status.busy": "2024-08-12T18:58:18.400844Z", - "iopub.status.idle": "2024-08-12T18:58:21.652442Z", - "shell.execute_reply": "2024-08-12T18:58:21.651832Z" + "iopub.execute_input": "2024-08-15T19:31:53.291629Z", + "iopub.status.busy": "2024-08-15T19:31:53.291118Z", + "iopub.status.idle": "2024-08-15T19:31:56.426128Z", + "shell.execute_reply": "2024-08-15T19:31:56.425611Z" }, "nbsphinx": "hidden" }, @@ -96,7 +96,7 @@ "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\" # disable parallelism to avoid deadlocks with huggingface\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -121,10 +121,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:21.654920Z", - "iopub.status.busy": "2024-08-12T18:58:21.654607Z", - "iopub.status.idle": "2024-08-12T18:58:21.658637Z", - "shell.execute_reply": "2024-08-12T18:58:21.658062Z" + "iopub.execute_input": "2024-08-15T19:31:56.428534Z", + "iopub.status.busy": "2024-08-15T19:31:56.428226Z", + "iopub.status.idle": "2024-08-15T19:31:56.431603Z", + "shell.execute_reply": "2024-08-15T19:31:56.431144Z" } }, "outputs": [], @@ -145,10 +145,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:21.660786Z", - "iopub.status.busy": "2024-08-12T18:58:21.660446Z", - "iopub.status.idle": "2024-08-12T18:58:21.663725Z", - "shell.execute_reply": "2024-08-12T18:58:21.663156Z" + "iopub.execute_input": "2024-08-15T19:31:56.433510Z", + "iopub.status.busy": "2024-08-15T19:31:56.433174Z", + "iopub.status.idle": "2024-08-15T19:31:56.436301Z", + "shell.execute_reply": "2024-08-15T19:31:56.435826Z" }, "nbsphinx": "hidden" }, @@ -178,10 +178,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:21.665708Z", - "iopub.status.busy": "2024-08-12T18:58:21.665531Z", - "iopub.status.idle": "2024-08-12T18:58:21.717461Z", - "shell.execute_reply": "2024-08-12T18:58:21.716912Z" + "iopub.execute_input": "2024-08-15T19:31:56.438277Z", + "iopub.status.busy": "2024-08-15T19:31:56.437938Z", + "iopub.status.idle": "2024-08-15T19:31:56.463233Z", + "shell.execute_reply": "2024-08-15T19:31:56.462763Z" } }, "outputs": [ @@ -271,10 +271,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:21.719763Z", - "iopub.status.busy": "2024-08-12T18:58:21.719394Z", - "iopub.status.idle": "2024-08-12T18:58:21.723483Z", - "shell.execute_reply": "2024-08-12T18:58:21.723002Z" + "iopub.execute_input": "2024-08-15T19:31:56.465244Z", + "iopub.status.busy": "2024-08-15T19:31:56.464906Z", + "iopub.status.idle": "2024-08-15T19:31:56.468662Z", + "shell.execute_reply": "2024-08-15T19:31:56.468108Z" } }, "outputs": [ @@ -283,7 +283,7 @@ "output_type": "stream", "text": [ "This dataset has 10 classes.\n", - "Classes: {'card_about_to_expire', 'supported_cards_and_currencies', 'apple_pay_or_google_pay', 'change_pin', 'beneficiary_not_allowed', 'getting_spare_card', 'visa_or_mastercard', 'cancel_transfer', 'lost_or_stolen_phone', 'card_payment_fee_charged'}\n" + "Classes: {'apple_pay_or_google_pay', 'cancel_transfer', 'card_about_to_expire', 'lost_or_stolen_phone', 'card_payment_fee_charged', 'change_pin', 'beneficiary_not_allowed', 'visa_or_mastercard', 'supported_cards_and_currencies', 'getting_spare_card'}\n" ] } ], @@ -307,10 +307,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:21.725660Z", - "iopub.status.busy": "2024-08-12T18:58:21.725307Z", - "iopub.status.idle": "2024-08-12T18:58:21.728467Z", - "shell.execute_reply": "2024-08-12T18:58:21.727871Z" + "iopub.execute_input": "2024-08-15T19:31:56.470853Z", + "iopub.status.busy": "2024-08-15T19:31:56.470459Z", + "iopub.status.idle": "2024-08-15T19:31:56.473643Z", + "shell.execute_reply": "2024-08-15T19:31:56.473126Z" } }, "outputs": [ @@ -365,10 +365,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:21.730586Z", - "iopub.status.busy": "2024-08-12T18:58:21.730242Z", - "iopub.status.idle": "2024-08-12T18:58:25.865055Z", - "shell.execute_reply": "2024-08-12T18:58:25.864467Z" + "iopub.execute_input": "2024-08-15T19:31:56.475663Z", + "iopub.status.busy": "2024-08-15T19:31:56.475357Z", + "iopub.status.idle": "2024-08-15T19:32:00.152853Z", + "shell.execute_reply": "2024-08-15T19:32:00.152235Z" } }, "outputs": [ @@ -416,10 +416,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:25.867863Z", - "iopub.status.busy": "2024-08-12T18:58:25.867442Z", - "iopub.status.idle": "2024-08-12T18:58:26.763555Z", - "shell.execute_reply": "2024-08-12T18:58:26.762971Z" + "iopub.execute_input": "2024-08-15T19:32:00.155721Z", + "iopub.status.busy": "2024-08-15T19:32:00.155322Z", + "iopub.status.idle": "2024-08-15T19:32:01.052440Z", + "shell.execute_reply": "2024-08-15T19:32:01.051858Z" }, "scrolled": true }, @@ -451,10 +451,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:26.767516Z", - "iopub.status.busy": "2024-08-12T18:58:26.766565Z", - "iopub.status.idle": "2024-08-12T18:58:26.770630Z", - "shell.execute_reply": "2024-08-12T18:58:26.770132Z" + "iopub.execute_input": "2024-08-15T19:32:01.055229Z", + "iopub.status.busy": "2024-08-15T19:32:01.054791Z", + "iopub.status.idle": "2024-08-15T19:32:01.057916Z", + "shell.execute_reply": "2024-08-15T19:32:01.057407Z" } }, "outputs": [], @@ -474,10 +474,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:26.773537Z", - "iopub.status.busy": "2024-08-12T18:58:26.773116Z", - "iopub.status.idle": "2024-08-12T18:58:28.849723Z", - "shell.execute_reply": "2024-08-12T18:58:28.849027Z" + "iopub.execute_input": "2024-08-15T19:32:01.061079Z", + "iopub.status.busy": "2024-08-15T19:32:01.060146Z", + "iopub.status.idle": "2024-08-15T19:32:03.017778Z", + "shell.execute_reply": "2024-08-15T19:32:03.017129Z" }, "scrolled": true }, @@ -521,10 +521,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.854134Z", - "iopub.status.busy": "2024-08-12T18:58:28.852936Z", - "iopub.status.idle": "2024-08-12T18:58:28.879769Z", - "shell.execute_reply": "2024-08-12T18:58:28.879212Z" + "iopub.execute_input": "2024-08-15T19:32:03.020919Z", + "iopub.status.busy": "2024-08-15T19:32:03.020370Z", + "iopub.status.idle": "2024-08-15T19:32:03.043484Z", + "shell.execute_reply": "2024-08-15T19:32:03.042975Z" }, "scrolled": true }, @@ -654,10 +654,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.883584Z", - "iopub.status.busy": "2024-08-12T18:58:28.882631Z", - "iopub.status.idle": "2024-08-12T18:58:28.891499Z", - "shell.execute_reply": "2024-08-12T18:58:28.890948Z" + "iopub.execute_input": "2024-08-15T19:32:03.046327Z", + "iopub.status.busy": "2024-08-15T19:32:03.046003Z", + "iopub.status.idle": "2024-08-15T19:32:03.055179Z", + "shell.execute_reply": "2024-08-15T19:32:03.054677Z" }, "scrolled": true }, @@ -767,10 +767,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.893482Z", - "iopub.status.busy": "2024-08-12T18:58:28.893306Z", - "iopub.status.idle": "2024-08-12T18:58:28.897763Z", - "shell.execute_reply": "2024-08-12T18:58:28.897181Z" + "iopub.execute_input": "2024-08-15T19:32:03.057402Z", + "iopub.status.busy": "2024-08-15T19:32:03.057090Z", + "iopub.status.idle": "2024-08-15T19:32:03.061065Z", + "shell.execute_reply": "2024-08-15T19:32:03.060602Z" } }, "outputs": [ @@ -808,10 +808,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.899997Z", - "iopub.status.busy": "2024-08-12T18:58:28.899647Z", - "iopub.status.idle": "2024-08-12T18:58:28.906101Z", - "shell.execute_reply": "2024-08-12T18:58:28.905560Z" + "iopub.execute_input": "2024-08-15T19:32:03.062929Z", + "iopub.status.busy": "2024-08-15T19:32:03.062734Z", + "iopub.status.idle": "2024-08-15T19:32:03.069884Z", + "shell.execute_reply": "2024-08-15T19:32:03.069438Z" } }, "outputs": [ @@ -928,10 +928,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.908389Z", - "iopub.status.busy": "2024-08-12T18:58:28.907947Z", - "iopub.status.idle": "2024-08-12T18:58:28.914961Z", - "shell.execute_reply": "2024-08-12T18:58:28.914528Z" + "iopub.execute_input": "2024-08-15T19:32:03.072112Z", + "iopub.status.busy": "2024-08-15T19:32:03.071664Z", + "iopub.status.idle": "2024-08-15T19:32:03.078249Z", + "shell.execute_reply": "2024-08-15T19:32:03.077794Z" } }, "outputs": [ @@ -1014,10 +1014,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.917187Z", - "iopub.status.busy": "2024-08-12T18:58:28.916621Z", - "iopub.status.idle": "2024-08-12T18:58:28.922611Z", - "shell.execute_reply": "2024-08-12T18:58:28.922057Z" + "iopub.execute_input": "2024-08-15T19:32:03.080256Z", + "iopub.status.busy": "2024-08-15T19:32:03.079945Z", + "iopub.status.idle": "2024-08-15T19:32:03.085647Z", + "shell.execute_reply": "2024-08-15T19:32:03.085108Z" } }, "outputs": [ @@ -1125,10 +1125,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.924669Z", - "iopub.status.busy": "2024-08-12T18:58:28.924332Z", - "iopub.status.idle": "2024-08-12T18:58:28.932890Z", - "shell.execute_reply": "2024-08-12T18:58:28.932312Z" + "iopub.execute_input": "2024-08-15T19:32:03.087737Z", + "iopub.status.busy": "2024-08-15T19:32:03.087410Z", + "iopub.status.idle": "2024-08-15T19:32:03.095505Z", + "shell.execute_reply": "2024-08-15T19:32:03.094954Z" } }, "outputs": [ @@ -1239,10 +1239,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.935108Z", - "iopub.status.busy": "2024-08-12T18:58:28.934598Z", - "iopub.status.idle": "2024-08-12T18:58:28.939954Z", - "shell.execute_reply": "2024-08-12T18:58:28.939509Z" + "iopub.execute_input": "2024-08-15T19:32:03.097391Z", + "iopub.status.busy": "2024-08-15T19:32:03.097120Z", + "iopub.status.idle": "2024-08-15T19:32:03.102354Z", + "shell.execute_reply": "2024-08-15T19:32:03.101837Z" } }, "outputs": [ @@ -1310,10 +1310,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.941972Z", - "iopub.status.busy": "2024-08-12T18:58:28.941648Z", - "iopub.status.idle": "2024-08-12T18:58:28.946967Z", - "shell.execute_reply": "2024-08-12T18:58:28.946427Z" + "iopub.execute_input": "2024-08-15T19:32:03.104472Z", + "iopub.status.busy": "2024-08-15T19:32:03.103996Z", + "iopub.status.idle": "2024-08-15T19:32:03.109400Z", + "shell.execute_reply": "2024-08-15T19:32:03.108853Z" } }, "outputs": [ @@ -1392,10 +1392,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.948895Z", - "iopub.status.busy": "2024-08-12T18:58:28.948718Z", - "iopub.status.idle": "2024-08-12T18:58:28.952461Z", - "shell.execute_reply": "2024-08-12T18:58:28.951982Z" + "iopub.execute_input": "2024-08-15T19:32:03.111465Z", + "iopub.status.busy": "2024-08-15T19:32:03.111165Z", + "iopub.status.idle": "2024-08-15T19:32:03.114499Z", + "shell.execute_reply": "2024-08-15T19:32:03.114003Z" } }, "outputs": [ @@ -1449,10 +1449,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:28.954958Z", - "iopub.status.busy": "2024-08-12T18:58:28.954419Z", - "iopub.status.idle": "2024-08-12T18:58:28.960190Z", - "shell.execute_reply": "2024-08-12T18:58:28.959744Z" + "iopub.execute_input": "2024-08-15T19:32:03.116556Z", + "iopub.status.busy": "2024-08-15T19:32:03.116226Z", + "iopub.status.idle": "2024-08-15T19:32:03.121395Z", + "shell.execute_reply": "2024-08-15T19:32:03.120973Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/datalab/workflows.html b/master/tutorials/datalab/workflows.html index 2b9558ba5..6435f3a60 100644 --- a/master/tutorials/datalab/workflows.html +++ b/master/tutorials/datalab/workflows.html @@ -833,7 +833,7 @@

    4. Identify Data Issues Using Datalab @@ -879,13 +879,13 @@

    4. Identify Data Issues Using Datalab - +
    - - - - - - - - - + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
     AgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_scoreAgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_score
    8nannannannannanNaTTrue0.000000
    1nanFemaleRural6421.1600005.000000NaTFalse0.666667
    9nanMaleRural4655.8200001.000000NaTFalse0.666667
    14nanMaleRural6790.4600003.000000NaTFalse0.666667
    13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
    15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
    056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
    246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
    332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
    460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
    525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
    638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
    756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
    1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
    1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
    1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.0000008nannannannannanNaTTrue0.000000
    1nanFemaleRural6421.1600005.000000NaTFalse0.666667
    9nanMaleRural4655.8200001.000000NaTFalse0.666667
    14nanMaleRural6790.4600003.000000NaTFalse0.666667
    13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
    15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
    056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
    246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
    332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
    460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
    525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
    638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
    756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
    1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
    1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
    1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.000000
    @@ -3503,16 +3503,16 @@

    1. Load the Dataset 
    ---2024-08-12 18:58:49--  https://s.cleanlab.ai/CIFAR-10-subset.zip
-Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.109.153, 185.199.110.153, 185.199.111.153, ...
-Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.109.153|:443... connected.
+--2024-08-15 19:32:23--  https://s.cleanlab.ai/CIFAR-10-subset.zip
+Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.111.153, 185.199.110.153, 185.199.109.153, ...
+Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.111.153|:443... connected.
 HTTP request sent, awaiting response... 200 OK
 Length: 986707 (964K) [application/zip]
 Saving to: ‘CIFAR-10-subset.zip’
 
-CIFAR-10-subset.zip 100%[===================>] 963.58K  --.-KB/s    in 0.04s
+CIFAR-10-subset.zip 100%[===================>] 963.58K  --.-KB/s    in 0.01s
 
-2024-08-12 18:58:49 (22.6 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]
+2024-08-15 19:32:23 (96.4 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]
    @@ -3582,7 +3582,7 @@

    2. Run Datalab Analysis
    -
    +
    @@ -3753,35 +3753,35 @@

    3. Interpret the Results - dark_score is_dark_issue + dark_score 0 - 0.237196 True + 0.237196 1 - 0.197229 True + 0.197229 2 - 0.254188 True + 0.254188 3 - 0.229170 True + 0.229170 4 - 0.208907 True + 0.208907 ... @@ -3790,28 +3790,28 @@

    3. Interpret the Results

    -
    +
    @@ -3986,35 +3986,35 @@

    4. (Optional) Compare with a Dataset Without Spurious Correlations - dark_score is_dark_issue + dark_score 0 - 0.797509 False + 0.797509 1 - 0.663760 False + 0.663760 2 - 0.849826 False + 0.849826 3 - 0.773951 False + 0.773951 4 - 0.699518 False + 0.699518 ... @@ -4023,28 +4023,28 @@

    4. (Optional) Compare with a Dataset Without Spurious Correlations

    You should notice that the original dataset has more balanced correlation scores and fewer (or no) issues related to darkness. This comparison highlights how spurious correlations can be detected by Datalab.

    diff --git a/master/tutorials/datalab/workflows.ipynb b/master/tutorials/datalab/workflows.ipynb index c19ab5d3e..02938d887 100644 --- a/master/tutorials/datalab/workflows.ipynb +++ b/master/tutorials/datalab/workflows.ipynb @@ -38,10 +38,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:32.453144Z", - "iopub.status.busy": "2024-08-12T18:58:32.452963Z", - "iopub.status.idle": "2024-08-12T18:58:32.893566Z", - "shell.execute_reply": "2024-08-12T18:58:32.892923Z" + "iopub.execute_input": "2024-08-15T19:32:07.448103Z", + "iopub.status.busy": "2024-08-15T19:32:07.447640Z", + "iopub.status.idle": "2024-08-15T19:32:07.871349Z", + "shell.execute_reply": "2024-08-15T19:32:07.870828Z" } }, "outputs": [], @@ -87,10 +87,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:32.896058Z", - "iopub.status.busy": "2024-08-12T18:58:32.895665Z", - "iopub.status.idle": "2024-08-12T18:58:33.028619Z", - "shell.execute_reply": "2024-08-12T18:58:33.028000Z" + "iopub.execute_input": "2024-08-15T19:32:07.873882Z", + "iopub.status.busy": "2024-08-15T19:32:07.873646Z", + "iopub.status.idle": "2024-08-15T19:32:08.002168Z", + "shell.execute_reply": "2024-08-15T19:32:08.001592Z" } }, "outputs": [ @@ -181,10 +181,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:33.030997Z", - "iopub.status.busy": "2024-08-12T18:58:33.030616Z", - "iopub.status.idle": "2024-08-12T18:58:33.053876Z", - "shell.execute_reply": "2024-08-12T18:58:33.053329Z" + "iopub.execute_input": "2024-08-15T19:32:08.004540Z", + "iopub.status.busy": "2024-08-15T19:32:08.004056Z", + "iopub.status.idle": "2024-08-15T19:32:08.026894Z", + "shell.execute_reply": "2024-08-15T19:32:08.026278Z" } }, "outputs": [], @@ -210,10 +210,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:33.056613Z", - "iopub.status.busy": "2024-08-12T18:58:33.056072Z", - "iopub.status.idle": "2024-08-12T18:58:36.368353Z", - "shell.execute_reply": "2024-08-12T18:58:36.367660Z" + "iopub.execute_input": "2024-08-15T19:32:08.029510Z", + "iopub.status.busy": "2024-08-15T19:32:08.029040Z", + "iopub.status.idle": "2024-08-15T19:32:11.204836Z", + "shell.execute_reply": "2024-08-15T19:32:11.204136Z" } }, "outputs": [ @@ -235,7 +235,7 @@ "Finding class_imbalance issues ...\n", "Finding underperforming_group issues ...\n", "\n", - "Audit complete. 523 issues found in the dataset.\n" + "Audit complete. 524 issues found in the dataset.\n" ] }, { @@ -280,13 +280,13 @@ " \n", " 2\n", " outlier\n", - " 0.356958\n", - " 362\n", + " 0.356925\n", + " 363\n", " \n", " \n", " 3\n", " near_duplicate\n", - " 0.619565\n", + " 0.619581\n", " 108\n", " \n", " \n", @@ -304,7 +304,7 @@ " \n", " 6\n", " underperforming_group\n", - " 0.651929\n", + " 0.651838\n", " 0\n", " \n", " \n", @@ -315,11 +315,11 @@ " issue_type score num_issues\n", "0 null 1.000000 0\n", "1 label 0.991400 52\n", - "2 outlier 0.356958 362\n", - "3 near_duplicate 0.619565 108\n", + "2 outlier 0.356925 363\n", + "3 near_duplicate 0.619581 108\n", "4 non_iid 0.000000 1\n", "5 class_imbalance 0.500000 0\n", - "6 underperforming_group 0.651929 0" + "6 underperforming_group 0.651838 0" ] }, "metadata": {}, @@ -700,10 +700,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:36.371024Z", - "iopub.status.busy": "2024-08-12T18:58:36.370494Z", - "iopub.status.idle": "2024-08-12T18:58:46.129472Z", - "shell.execute_reply": "2024-08-12T18:58:46.128923Z" + "iopub.execute_input": "2024-08-15T19:32:11.207672Z", + "iopub.status.busy": "2024-08-15T19:32:11.207175Z", + "iopub.status.idle": "2024-08-15T19:32:20.088677Z", + "shell.execute_reply": "2024-08-15T19:32:20.088072Z" } }, "outputs": [ @@ -804,10 +804,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:46.131756Z", - "iopub.status.busy": "2024-08-12T18:58:46.131373Z", - "iopub.status.idle": "2024-08-12T18:58:46.324220Z", - "shell.execute_reply": "2024-08-12T18:58:46.323687Z" + "iopub.execute_input": "2024-08-15T19:32:20.091002Z", + "iopub.status.busy": "2024-08-15T19:32:20.090656Z", + "iopub.status.idle": "2024-08-15T19:32:20.248704Z", + "shell.execute_reply": "2024-08-15T19:32:20.248045Z" } }, "outputs": [], @@ -838,10 +838,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:46.326841Z", - "iopub.status.busy": "2024-08-12T18:58:46.326478Z", - "iopub.status.idle": "2024-08-12T18:58:47.671516Z", - "shell.execute_reply": "2024-08-12T18:58:47.670901Z" + "iopub.execute_input": "2024-08-15T19:32:20.251411Z", + "iopub.status.busy": "2024-08-15T19:32:20.251052Z", + "iopub.status.idle": "2024-08-15T19:32:21.792486Z", + "shell.execute_reply": "2024-08-15T19:32:21.791991Z" } }, "outputs": [ @@ -1000,10 +1000,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:47.673692Z", - "iopub.status.busy": "2024-08-12T18:58:47.673500Z", - "iopub.status.idle": "2024-08-12T18:58:48.008455Z", - "shell.execute_reply": "2024-08-12T18:58:48.007859Z" + "iopub.execute_input": "2024-08-15T19:32:21.794774Z", + "iopub.status.busy": "2024-08-15T19:32:21.794323Z", + "iopub.status.idle": "2024-08-15T19:32:22.022639Z", + "shell.execute_reply": "2024-08-15T19:32:22.022068Z" } }, "outputs": [ @@ -1082,10 +1082,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.010951Z", - "iopub.status.busy": "2024-08-12T18:58:48.010444Z", - "iopub.status.idle": "2024-08-12T18:58:48.023807Z", - "shell.execute_reply": "2024-08-12T18:58:48.023327Z" + "iopub.execute_input": "2024-08-15T19:32:22.025206Z", + "iopub.status.busy": "2024-08-15T19:32:22.024772Z", + "iopub.status.idle": "2024-08-15T19:32:22.037394Z", + "shell.execute_reply": "2024-08-15T19:32:22.036948Z" } }, "outputs": [], @@ -1115,10 +1115,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.025787Z", - "iopub.status.busy": "2024-08-12T18:58:48.025610Z", - "iopub.status.idle": "2024-08-12T18:58:48.044448Z", - "shell.execute_reply": "2024-08-12T18:58:48.043957Z" + "iopub.execute_input": "2024-08-15T19:32:22.039465Z", + "iopub.status.busy": "2024-08-15T19:32:22.039034Z", + "iopub.status.idle": "2024-08-15T19:32:22.057890Z", + "shell.execute_reply": "2024-08-15T19:32:22.057315Z" } }, "outputs": [], @@ -1146,10 +1146,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.046497Z", - "iopub.status.busy": "2024-08-12T18:58:48.046158Z", - "iopub.status.idle": "2024-08-12T18:58:48.285984Z", - "shell.execute_reply": "2024-08-12T18:58:48.285450Z" + "iopub.execute_input": "2024-08-15T19:32:22.060271Z", + "iopub.status.busy": "2024-08-15T19:32:22.059831Z", + "iopub.status.idle": "2024-08-15T19:32:22.272307Z", + "shell.execute_reply": "2024-08-15T19:32:22.271782Z" } }, "outputs": [], @@ -1189,10 +1189,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.288600Z", - "iopub.status.busy": "2024-08-12T18:58:48.288414Z", - "iopub.status.idle": "2024-08-12T18:58:48.307909Z", - "shell.execute_reply": "2024-08-12T18:58:48.307390Z" + "iopub.execute_input": "2024-08-15T19:32:22.274914Z", + "iopub.status.busy": "2024-08-15T19:32:22.274506Z", + "iopub.status.idle": "2024-08-15T19:32:22.294460Z", + "shell.execute_reply": "2024-08-15T19:32:22.293989Z" } }, "outputs": [ @@ -1390,10 +1390,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.310085Z", - "iopub.status.busy": "2024-08-12T18:58:48.309902Z", - "iopub.status.idle": "2024-08-12T18:58:48.479863Z", - "shell.execute_reply": "2024-08-12T18:58:48.479263Z" + "iopub.execute_input": "2024-08-15T19:32:22.296540Z", + "iopub.status.busy": "2024-08-15T19:32:22.296201Z", + "iopub.status.idle": "2024-08-15T19:32:22.462255Z", + "shell.execute_reply": "2024-08-15T19:32:22.461728Z" } }, "outputs": [ @@ -1460,10 +1460,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.482094Z", - "iopub.status.busy": "2024-08-12T18:58:48.481913Z", - "iopub.status.idle": "2024-08-12T18:58:48.492262Z", - "shell.execute_reply": "2024-08-12T18:58:48.491815Z" + "iopub.execute_input": "2024-08-15T19:32:22.464546Z", + "iopub.status.busy": "2024-08-15T19:32:22.464363Z", + "iopub.status.idle": "2024-08-15T19:32:22.474373Z", + "shell.execute_reply": "2024-08-15T19:32:22.473823Z" } }, "outputs": [ @@ -1729,10 +1729,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.494349Z", - "iopub.status.busy": "2024-08-12T18:58:48.494005Z", - "iopub.status.idle": "2024-08-12T18:58:48.503362Z", - "shell.execute_reply": "2024-08-12T18:58:48.502898Z" + "iopub.execute_input": "2024-08-15T19:32:22.476496Z", + "iopub.status.busy": "2024-08-15T19:32:22.476158Z", + "iopub.status.idle": "2024-08-15T19:32:22.485421Z", + "shell.execute_reply": "2024-08-15T19:32:22.484953Z" } }, "outputs": [ @@ -1919,10 +1919,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.505548Z", - "iopub.status.busy": "2024-08-12T18:58:48.505209Z", - "iopub.status.idle": "2024-08-12T18:58:48.530999Z", - "shell.execute_reply": "2024-08-12T18:58:48.530573Z" + "iopub.execute_input": "2024-08-15T19:32:22.487349Z", + "iopub.status.busy": "2024-08-15T19:32:22.487074Z", + "iopub.status.idle": "2024-08-15T19:32:22.513874Z", + "shell.execute_reply": "2024-08-15T19:32:22.513299Z" } }, "outputs": [], @@ -1956,10 +1956,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.533100Z", - "iopub.status.busy": "2024-08-12T18:58:48.532754Z", - "iopub.status.idle": "2024-08-12T18:58:48.535405Z", - "shell.execute_reply": "2024-08-12T18:58:48.534950Z" + "iopub.execute_input": "2024-08-15T19:32:22.516166Z", + "iopub.status.busy": "2024-08-15T19:32:22.515857Z", + "iopub.status.idle": "2024-08-15T19:32:22.518726Z", + "shell.execute_reply": "2024-08-15T19:32:22.518159Z" } }, "outputs": [], @@ -1981,10 +1981,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.537559Z", - "iopub.status.busy": "2024-08-12T18:58:48.537229Z", - "iopub.status.idle": "2024-08-12T18:58:48.557131Z", - "shell.execute_reply": "2024-08-12T18:58:48.556530Z" + "iopub.execute_input": "2024-08-15T19:32:22.520685Z", + "iopub.status.busy": "2024-08-15T19:32:22.520510Z", + "iopub.status.idle": "2024-08-15T19:32:22.540384Z", + "shell.execute_reply": "2024-08-15T19:32:22.539835Z" } }, "outputs": [ @@ -2142,10 +2142,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.559284Z", - "iopub.status.busy": "2024-08-12T18:58:48.559093Z", - "iopub.status.idle": "2024-08-12T18:58:48.563631Z", - "shell.execute_reply": "2024-08-12T18:58:48.563160Z" + "iopub.execute_input": "2024-08-15T19:32:22.542488Z", + "iopub.status.busy": "2024-08-15T19:32:22.542086Z", + "iopub.status.idle": "2024-08-15T19:32:22.546531Z", + "shell.execute_reply": "2024-08-15T19:32:22.546068Z" } }, "outputs": [], @@ -2178,10 +2178,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.565611Z", - "iopub.status.busy": "2024-08-12T18:58:48.565430Z", - "iopub.status.idle": "2024-08-12T18:58:48.594740Z", - "shell.execute_reply": "2024-08-12T18:58:48.594193Z" + "iopub.execute_input": "2024-08-15T19:32:22.548504Z", + "iopub.status.busy": "2024-08-15T19:32:22.548199Z", + "iopub.status.idle": "2024-08-15T19:32:22.575378Z", + "shell.execute_reply": "2024-08-15T19:32:22.574805Z" } }, "outputs": [ @@ -2327,10 +2327,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.596930Z", - "iopub.status.busy": "2024-08-12T18:58:48.596743Z", - "iopub.status.idle": "2024-08-12T18:58:48.915286Z", - "shell.execute_reply": "2024-08-12T18:58:48.914655Z" + "iopub.execute_input": "2024-08-15T19:32:22.577490Z", + "iopub.status.busy": "2024-08-15T19:32:22.577100Z", + "iopub.status.idle": "2024-08-15T19:32:22.944617Z", + "shell.execute_reply": "2024-08-15T19:32:22.944050Z" } }, "outputs": [ @@ -2397,10 +2397,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.917554Z", - "iopub.status.busy": "2024-08-12T18:58:48.917331Z", - "iopub.status.idle": "2024-08-12T18:58:48.920951Z", - "shell.execute_reply": "2024-08-12T18:58:48.920337Z" + "iopub.execute_input": "2024-08-15T19:32:22.946769Z", + "iopub.status.busy": "2024-08-15T19:32:22.946457Z", + "iopub.status.idle": "2024-08-15T19:32:22.949952Z", + "shell.execute_reply": "2024-08-15T19:32:22.949480Z" } }, "outputs": [ @@ -2451,10 +2451,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.923307Z", - "iopub.status.busy": "2024-08-12T18:58:48.922856Z", - "iopub.status.idle": "2024-08-12T18:58:48.936475Z", - "shell.execute_reply": "2024-08-12T18:58:48.935867Z" + "iopub.execute_input": "2024-08-15T19:32:22.952098Z", + "iopub.status.busy": "2024-08-15T19:32:22.951804Z", + "iopub.status.idle": "2024-08-15T19:32:22.965735Z", + "shell.execute_reply": "2024-08-15T19:32:22.965243Z" } }, "outputs": [ @@ -2733,10 +2733,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.939768Z", - "iopub.status.busy": "2024-08-12T18:58:48.939280Z", - "iopub.status.idle": "2024-08-12T18:58:48.953750Z", - "shell.execute_reply": "2024-08-12T18:58:48.953140Z" + "iopub.execute_input": "2024-08-15T19:32:22.968006Z", + "iopub.status.busy": "2024-08-15T19:32:22.967638Z", + "iopub.status.idle": "2024-08-15T19:32:22.986177Z", + "shell.execute_reply": "2024-08-15T19:32:22.985680Z" } }, "outputs": [ @@ -3003,10 +3003,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.955892Z", - "iopub.status.busy": "2024-08-12T18:58:48.955606Z", - "iopub.status.idle": "2024-08-12T18:58:48.966964Z", - "shell.execute_reply": "2024-08-12T18:58:48.966339Z" + "iopub.execute_input": "2024-08-15T19:32:22.988339Z", + "iopub.status.busy": "2024-08-15T19:32:22.988017Z", + "iopub.status.idle": "2024-08-15T19:32:22.998153Z", + "shell.execute_reply": "2024-08-15T19:32:22.997710Z" } }, "outputs": [], @@ -3031,10 +3031,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.969417Z", - "iopub.status.busy": "2024-08-12T18:58:48.969078Z", - "iopub.status.idle": "2024-08-12T18:58:48.978995Z", - "shell.execute_reply": "2024-08-12T18:58:48.978417Z" + "iopub.execute_input": "2024-08-15T19:32:23.000127Z", + "iopub.status.busy": "2024-08-15T19:32:22.999821Z", + "iopub.status.idle": "2024-08-15T19:32:23.008900Z", + "shell.execute_reply": "2024-08-15T19:32:23.008362Z" } }, "outputs": [ @@ -3206,10 +3206,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.981220Z", - "iopub.status.busy": "2024-08-12T18:58:48.980883Z", - "iopub.status.idle": "2024-08-12T18:58:48.984861Z", - "shell.execute_reply": "2024-08-12T18:58:48.984275Z" + "iopub.execute_input": "2024-08-15T19:32:23.011136Z", + "iopub.status.busy": "2024-08-15T19:32:23.010689Z", + "iopub.status.idle": "2024-08-15T19:32:23.014343Z", + "shell.execute_reply": "2024-08-15T19:32:23.013789Z" } }, "outputs": [], @@ -3241,10 +3241,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:48.986942Z", - "iopub.status.busy": "2024-08-12T18:58:48.986600Z", - "iopub.status.idle": "2024-08-12T18:58:49.039015Z", - "shell.execute_reply": "2024-08-12T18:58:49.038408Z" + "iopub.execute_input": "2024-08-15T19:32:23.016304Z", + "iopub.status.busy": "2024-08-15T19:32:23.016009Z", + "iopub.status.idle": "2024-08-15T19:32:23.066545Z", + "shell.execute_reply": "2024-08-15T19:32:23.066076Z" } }, "outputs": [ @@ -3252,230 +3252,230 @@ "data": { "text/html": [ "\n", - 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    \n" ], "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -3551,10 +3551,10 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:49.041588Z", - "iopub.status.busy": "2024-08-12T18:58:49.041136Z", - "iopub.status.idle": "2024-08-12T18:58:49.048316Z", - "shell.execute_reply": "2024-08-12T18:58:49.047854Z" + "iopub.execute_input": "2024-08-15T19:32:23.068763Z", + "iopub.status.busy": "2024-08-15T19:32:23.068340Z", + "iopub.status.idle": "2024-08-15T19:32:23.074789Z", + "shell.execute_reply": "2024-08-15T19:32:23.074339Z" } }, "outputs": [], @@ -3593,10 +3593,10 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:49.050457Z", - "iopub.status.busy": "2024-08-12T18:58:49.050118Z", - "iopub.status.idle": "2024-08-12T18:58:49.061463Z", - "shell.execute_reply": "2024-08-12T18:58:49.060888Z" + "iopub.execute_input": "2024-08-15T19:32:23.076818Z", + "iopub.status.busy": "2024-08-15T19:32:23.076478Z", + "iopub.status.idle": "2024-08-15T19:32:23.087561Z", + "shell.execute_reply": "2024-08-15T19:32:23.087094Z" } }, "outputs": [ @@ -3632,10 +3632,10 @@ "execution_count": 31, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:49.063774Z", - "iopub.status.busy": "2024-08-12T18:58:49.063445Z", - "iopub.status.idle": "2024-08-12T18:58:49.282520Z", - "shell.execute_reply": "2024-08-12T18:58:49.281931Z" + "iopub.execute_input": "2024-08-15T19:32:23.089553Z", + "iopub.status.busy": "2024-08-15T19:32:23.089220Z", + "iopub.status.idle": "2024-08-15T19:32:23.301895Z", + "shell.execute_reply": "2024-08-15T19:32:23.301343Z" } }, "outputs": [ @@ -3687,10 +3687,10 @@ "execution_count": 32, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:49.284947Z", - "iopub.status.busy": "2024-08-12T18:58:49.284525Z", - "iopub.status.idle": "2024-08-12T18:58:49.292566Z", - "shell.execute_reply": "2024-08-12T18:58:49.292062Z" + "iopub.execute_input": "2024-08-15T19:32:23.303959Z", + "iopub.status.busy": "2024-08-15T19:32:23.303642Z", + "iopub.status.idle": "2024-08-15T19:32:23.311114Z", + "shell.execute_reply": "2024-08-15T19:32:23.310546Z" }, "nbsphinx": "hidden" }, @@ -3756,10 +3756,10 @@ "execution_count": 33, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:49.294849Z", - "iopub.status.busy": "2024-08-12T18:58:49.294514Z", - "iopub.status.idle": "2024-08-12T18:58:49.928407Z", - "shell.execute_reply": "2024-08-12T18:58:49.927648Z" + "iopub.execute_input": "2024-08-15T19:32:23.313166Z", + "iopub.status.busy": "2024-08-15T19:32:23.312837Z", + "iopub.status.idle": "2024-08-15T19:32:23.678819Z", + "shell.execute_reply": "2024-08-15T19:32:23.678171Z" } }, "outputs": [ @@ -3767,9 +3767,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-08-12 18:58:49-- https://s.cleanlab.ai/CIFAR-10-subset.zip\r\n", - "Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.109.153, 185.199.110.153, 185.199.111.153, ...\r\n", - "Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.109.153|:443... connected.\r\n", + "--2024-08-15 19:32:23-- https://s.cleanlab.ai/CIFAR-10-subset.zip\r\n", + "Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.111.153, 185.199.110.153, 185.199.109.153, ...\r\n", + "Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.111.153|:443... connected.\r\n", "HTTP request sent, awaiting response... " ] }, @@ -3783,9 +3783,9 @@ "\r\n", "\r", "CIFAR-10-subset.zip 0%[ ] 0 --.-KB/s \r", - "CIFAR-10-subset.zip 100%[===================>] 963.58K --.-KB/s in 0.04s \r\n", + "CIFAR-10-subset.zip 100%[===================>] 963.58K --.-KB/s in 0.01s \r\n", "\r\n", - "2024-08-12 18:58:49 (22.6 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]\r\n", + "2024-08-15 19:32:23 (96.4 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]\r\n", "\r\n" ] } @@ -3801,10 +3801,10 @@ "execution_count": 34, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:49.931184Z", - "iopub.status.busy": "2024-08-12T18:58:49.930775Z", - "iopub.status.idle": "2024-08-12T18:58:51.929317Z", - "shell.execute_reply": "2024-08-12T18:58:51.928757Z" + "iopub.execute_input": "2024-08-15T19:32:23.681484Z", + "iopub.status.busy": "2024-08-15T19:32:23.681045Z", + "iopub.status.idle": "2024-08-15T19:32:25.595990Z", + "shell.execute_reply": "2024-08-15T19:32:25.595452Z" } }, "outputs": [], @@ -3850,10 +3850,10 @@ "execution_count": 35, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:51.932133Z", - "iopub.status.busy": "2024-08-12T18:58:51.931579Z", - "iopub.status.idle": "2024-08-12T18:58:52.415840Z", - "shell.execute_reply": "2024-08-12T18:58:52.415213Z" + "iopub.execute_input": "2024-08-15T19:32:25.598644Z", + "iopub.status.busy": "2024-08-15T19:32:25.598216Z", + "iopub.status.idle": "2024-08-15T19:32:26.054920Z", + "shell.execute_reply": "2024-08-15T19:32:26.054323Z" } }, "outputs": [ @@ -3868,7 +3868,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c0b69f70cccc4c2cb212d2804eaaa895", + "model_id": "bf66a8ee7a6b493592553e18b6727869", "version_major": 2, "version_minor": 0 }, @@ -3950,10 +3950,10 @@ "execution_count": 36, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:52.419360Z", - "iopub.status.busy": "2024-08-12T18:58:52.418978Z", - "iopub.status.idle": "2024-08-12T18:58:52.433093Z", - "shell.execute_reply": "2024-08-12T18:58:52.432477Z" + "iopub.execute_input": "2024-08-15T19:32:26.057885Z", + "iopub.status.busy": "2024-08-15T19:32:26.057548Z", + "iopub.status.idle": "2024-08-15T19:32:26.074641Z", + "shell.execute_reply": "2024-08-15T19:32:26.074093Z" } }, "outputs": [ @@ -4072,35 +4072,35 @@ " \n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 0\n", - " 0.237196\n", " True\n", + " 0.237196\n", " \n", " \n", " 1\n", - " 0.197229\n", " True\n", + " 0.197229\n", " \n", " \n", " 2\n", - " 0.254188\n", " True\n", + " 0.254188\n", " \n", " \n", " 3\n", - " 0.229170\n", " True\n", + " 0.229170\n", " \n", " \n", " 4\n", - " 0.208907\n", " True\n", + " 0.208907\n", " \n", " \n", " ...\n", @@ -4109,28 +4109,28 @@ " \n", " \n", " 195\n", - " 0.793840\n", " False\n", + " 0.793840\n", " \n", " \n", " 196\n", - " 1.000000\n", " False\n", + " 1.000000\n", " \n", " \n", " 197\n", - " 0.971560\n", " False\n", + " 0.971560\n", " \n", " \n", " 198\n", - " 0.862236\n", " False\n", + " 0.862236\n", " \n", " \n", " 199\n", - " 0.973533\n", " False\n", + " 0.973533\n", " \n", " \n", "\n", @@ -4138,18 +4138,18 @@ "

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    " ], "text/plain": [ - " dark_score is_dark_issue\n", - "0 0.797509 False\n", - "1 0.663760 False\n", - "2 0.849826 False\n", - "3 0.773951 False\n", - "4 0.699518 False\n", - ".. ... ...\n", - "195 0.793840 False\n", - "196 1.000000 False\n", - "197 0.971560 False\n", - "198 0.862236 False\n", - "199 0.973533 False\n", + " is_dark_issue dark_score\n", + "0 False 0.797509\n", + "1 False 0.663760\n", + "2 False 0.849826\n", + "3 False 0.773951\n", + "4 False 0.699518\n", + ".. ... ...\n", + "195 False 0.793840\n", + "196 False 1.000000\n", + "197 False 0.971560\n", + "198 False 0.862236\n", + "199 False 0.973533\n", "\n", "[200 rows x 2 columns]" ] @@ -4497,7 +4497,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "0a1d4a795cea4368bfe801319f6bfa56": { + "05a6d45db56d47d29f94784604013728": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4550,7 +4550,25 @@ "width": null } }, - "15abb84193a243528666ebc7929e204b": { + "06621f1db310446cb2967f1a1074f27c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "13b0bfd383ce4cad97bd56824d09289d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -4565,33 +4583,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_629b3803f80f47f78a312e9773869e99", + "layout": "IPY_MODEL_05a6d45db56d47d29f94784604013728", "placeholder": "​", - "style": "IPY_MODEL_d50b005bb100446d8effbbe10def949d", + "style": "IPY_MODEL_ffec4e0efbda45eca9a987d98c20b036", "tabbable": null, "tooltip": null, - "value": "100%" + "value": " 200/200 [00:00<00:00, 788.92it/s]" } }, - "24c54c690ba349a98a6611f44fc4e1cd": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "31387dc410ba4ac08097c6cdf1214b46": { + "19e32957e3b0467c93b11b121a2f32a9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4644,23 +4644,80 @@ "width": null } }, - 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"background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_19e32957e3b0467c93b11b121a2f32a9", + "placeholder": "​", + "style": "IPY_MODEL_7d9cbc24b6ba4fca98ca8bb3463d3724", + "tabbable": null, + "tooltip": null, + "value": "100%" } }, - "d8bdbf2497dd4a7aaec510ff6b6969d7": { + "df4f1364e119421b9c615bcb06aacea9": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5107,15 +5112,41 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_0a1d4a795cea4368bfe801319f6bfa56", + "layout": "IPY_MODEL_6453d2d2a05242f1a9af375e08d6f1ee", "placeholder": "​", - "style": "IPY_MODEL_48c731e8cf064b9784b5dd2b4d6be5de", + "style": "IPY_MODEL_06621f1db310446cb2967f1a1074f27c", "tabbable": null, "tooltip": null, "value": "100%" } }, - "e451cadbebfe41029d5d3cb34c96f9d0": { + "edad3d2c1723480a85c96a2d4901ffe6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_f1f1660f3de7459cae99a7f31370d99a", + "max": 200.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_b9e85b1062cd478682a6a82691d20546", + "tabbable": null, + "tooltip": null, + "value": 200.0 + } + }, + "f1f1660f3de7459cae99a7f31370d99a": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5168,53 +5199,22 @@ "width": null } }, - "e7cff525d0ed4da79ea4db12e670ea42": { + "ffec4e0efbda45eca9a987d98c20b036": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_31387dc410ba4ac08097c6cdf1214b46", - "placeholder": "​", - "style": "IPY_MODEL_24c54c690ba349a98a6611f44fc4e1cd", - "tabbable": null, - "tooltip": null, - "value": " 200/200 [00:00<00:00, 753.06it/s]" - } - }, - "fc333b4698444611a9ef2c362a197831": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_419e162125f94925b4776a8268ab2f13", - "max": 200.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_b11b3fa000794406af4de521bf6381e4", - "tabbable": null, - "tooltip": null, - "value": 200.0 + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } } }, diff --git a/master/tutorials/dataset_health.ipynb b/master/tutorials/dataset_health.ipynb index a972cd809..a30bdf687 100644 --- a/master/tutorials/dataset_health.ipynb +++ b/master/tutorials/dataset_health.ipynb @@ -70,10 +70,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:57.416743Z", - "iopub.status.busy": "2024-08-12T18:58:57.416562Z", - "iopub.status.idle": "2024-08-12T18:58:58.889432Z", - "shell.execute_reply": "2024-08-12T18:58:58.888841Z" + "iopub.execute_input": "2024-08-15T19:32:30.764696Z", + "iopub.status.busy": "2024-08-15T19:32:30.764524Z", + "iopub.status.idle": "2024-08-15T19:32:32.148355Z", + "shell.execute_reply": "2024-08-15T19:32:32.147808Z" }, "nbsphinx": "hidden" }, @@ -85,7 +85,7 @@ "dependencies = [\"cleanlab\", \"requests\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -110,10 +110,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:58.892133Z", - "iopub.status.busy": "2024-08-12T18:58:58.891633Z", - "iopub.status.idle": "2024-08-12T18:58:58.894507Z", - "shell.execute_reply": "2024-08-12T18:58:58.894046Z" + "iopub.execute_input": "2024-08-15T19:32:32.151057Z", + "iopub.status.busy": "2024-08-15T19:32:32.150540Z", + "iopub.status.idle": "2024-08-15T19:32:32.153292Z", + "shell.execute_reply": "2024-08-15T19:32:32.152850Z" }, "id": "_UvI80l42iyi" }, @@ -203,10 +203,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:58.896557Z", - "iopub.status.busy": "2024-08-12T18:58:58.896376Z", - "iopub.status.idle": "2024-08-12T18:58:58.908772Z", - "shell.execute_reply": "2024-08-12T18:58:58.908263Z" + "iopub.execute_input": "2024-08-15T19:32:32.155557Z", + "iopub.status.busy": "2024-08-15T19:32:32.155159Z", + "iopub.status.idle": "2024-08-15T19:32:32.167629Z", + "shell.execute_reply": "2024-08-15T19:32:32.167128Z" }, "nbsphinx": "hidden" }, @@ -285,10 +285,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:58:58.910826Z", - "iopub.status.busy": "2024-08-12T18:58:58.910636Z", - "iopub.status.idle": "2024-08-12T18:59:06.267643Z", - "shell.execute_reply": "2024-08-12T18:59:06.267042Z" + "iopub.execute_input": "2024-08-15T19:32:32.169845Z", + "iopub.status.busy": "2024-08-15T19:32:32.169477Z", + "iopub.status.idle": "2024-08-15T19:32:38.766430Z", + "shell.execute_reply": "2024-08-15T19:32:38.765838Z" }, "id": "dhTHOg8Pyv5G" }, diff --git a/master/tutorials/faq.html b/master/tutorials/faq.html index 800d8f271..378e1602e 100644 --- a/master/tutorials/faq.html +++ b/master/tutorials/faq.html @@ -831,13 +831,13 @@

    How can I find label issues in big datasets with limited memory?
    -
    +
    -
    +
    @@ -1702,7 +1702,7 @@

    Can’t find an answer to your question?new Github issue. Our developers may also provide personalized assistance in our Slack Community.

    Professional support and services are also available from our ML experts, learn more by emailing: team@cleanlab.ai

    diff --git a/master/tutorials/faq.ipynb b/master/tutorials/faq.ipynb index 82cd5d47d..2e179180f 100644 --- a/master/tutorials/faq.ipynb +++ b/master/tutorials/faq.ipynb @@ -18,10 +18,10 @@ "id": "2a4efdde", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:09.036162Z", - "iopub.status.busy": "2024-08-12T18:59:09.035980Z", - "iopub.status.idle": "2024-08-12T18:59:10.530018Z", - "shell.execute_reply": "2024-08-12T18:59:10.529347Z" + "iopub.execute_input": "2024-08-15T19:32:41.083193Z", + "iopub.status.busy": "2024-08-15T19:32:41.083028Z", + "iopub.status.idle": "2024-08-15T19:32:42.450599Z", + "shell.execute_reply": "2024-08-15T19:32:42.449954Z" }, "nbsphinx": "hidden" }, @@ -137,10 +137,10 @@ "id": "239d5ee7", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:10.532800Z", - "iopub.status.busy": "2024-08-12T18:59:10.532485Z", - "iopub.status.idle": "2024-08-12T18:59:10.536043Z", - "shell.execute_reply": "2024-08-12T18:59:10.535464Z" + "iopub.execute_input": "2024-08-15T19:32:42.453193Z", + "iopub.status.busy": "2024-08-15T19:32:42.452895Z", + "iopub.status.idle": "2024-08-15T19:32:42.456316Z", + "shell.execute_reply": "2024-08-15T19:32:42.455755Z" } }, "outputs": [], @@ -176,10 +176,10 @@ "id": "28b324aa", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:10.538323Z", - "iopub.status.busy": "2024-08-12T18:59:10.537990Z", - "iopub.status.idle": "2024-08-12T18:59:14.370319Z", - "shell.execute_reply": "2024-08-12T18:59:14.369463Z" + "iopub.execute_input": "2024-08-15T19:32:42.458321Z", + "iopub.status.busy": "2024-08-15T19:32:42.458000Z", + "iopub.status.idle": "2024-08-15T19:32:45.975200Z", + "shell.execute_reply": "2024-08-15T19:32:45.974500Z" } }, "outputs": [], @@ -202,10 +202,10 @@ "id": "28b324ab", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:14.374238Z", - "iopub.status.busy": "2024-08-12T18:59:14.373122Z", - "iopub.status.idle": "2024-08-12T18:59:14.430561Z", - "shell.execute_reply": "2024-08-12T18:59:14.429766Z" + "iopub.execute_input": "2024-08-15T19:32:45.978244Z", + "iopub.status.busy": "2024-08-15T19:32:45.977554Z", + "iopub.status.idle": "2024-08-15T19:32:46.018915Z", + "shell.execute_reply": "2024-08-15T19:32:46.018260Z" } }, "outputs": [], @@ -228,10 +228,10 @@ "id": "90c10e18", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:14.433816Z", - "iopub.status.busy": "2024-08-12T18:59:14.433400Z", - "iopub.status.idle": "2024-08-12T18:59:14.483159Z", - "shell.execute_reply": "2024-08-12T18:59:14.482495Z" + "iopub.execute_input": "2024-08-15T19:32:46.021645Z", + "iopub.status.busy": "2024-08-15T19:32:46.021328Z", + "iopub.status.idle": "2024-08-15T19:32:46.062898Z", + "shell.execute_reply": "2024-08-15T19:32:46.062144Z" } }, "outputs": [], @@ -253,10 +253,10 @@ "id": "88839519", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:14.485853Z", - "iopub.status.busy": "2024-08-12T18:59:14.485594Z", - "iopub.status.idle": "2024-08-12T18:59:14.488767Z", - "shell.execute_reply": "2024-08-12T18:59:14.488266Z" + "iopub.execute_input": "2024-08-15T19:32:46.065862Z", + "iopub.status.busy": "2024-08-15T19:32:46.065352Z", + "iopub.status.idle": "2024-08-15T19:32:46.068668Z", + "shell.execute_reply": "2024-08-15T19:32:46.068103Z" } }, "outputs": [], @@ -278,10 +278,10 @@ "id": "558490c2", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:14.490990Z", - "iopub.status.busy": "2024-08-12T18:59:14.490655Z", - "iopub.status.idle": "2024-08-12T18:59:14.493275Z", - "shell.execute_reply": "2024-08-12T18:59:14.492800Z" + "iopub.execute_input": "2024-08-15T19:32:46.070916Z", + "iopub.status.busy": "2024-08-15T19:32:46.070471Z", + "iopub.status.idle": "2024-08-15T19:32:46.073248Z", + "shell.execute_reply": "2024-08-15T19:32:46.072705Z" } }, "outputs": [], @@ -363,10 +363,10 @@ "id": "41714b51", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:14.495455Z", - "iopub.status.busy": "2024-08-12T18:59:14.495115Z", - "iopub.status.idle": "2024-08-12T18:59:14.521134Z", - "shell.execute_reply": "2024-08-12T18:59:14.520510Z" + "iopub.execute_input": "2024-08-15T19:32:46.075413Z", + "iopub.status.busy": "2024-08-15T19:32:46.075107Z", + "iopub.status.idle": "2024-08-15T19:32:46.099170Z", + "shell.execute_reply": "2024-08-15T19:32:46.098621Z" } }, "outputs": [ @@ -380,7 +380,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"id": "7596b65c", + "id": "7a8509f0", "metadata": {}, "source": [ "### How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?" @@ -1327,7 +1327,7 @@ }, { "cell_type": "markdown", - "id": "8cd71820", + "id": "3dff8396", "metadata": {}, "source": [ "The instructions for specifying pre-computed data slices/clusters when detecting underperforming groups in a dataset are now covered in detail in the Datalab workflows tutorial.\n", @@ -1338,7 +1338,7 @@ }, { "cell_type": "markdown", - "id": "74548889", + "id": "6a113536", "metadata": {}, "source": [ "### How to handle near-duplicate data identified by Datalab?\n", @@ -1349,13 +1349,13 @@ { "cell_type": "code", "execution_count": 18, - "id": "06b1a332", + "id": "604600db", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:18.004021Z", - "iopub.status.busy": "2024-08-12T18:59:18.003656Z", - "iopub.status.idle": "2024-08-12T18:59:18.011463Z", - "shell.execute_reply": "2024-08-12T18:59:18.010982Z" + "iopub.execute_input": "2024-08-15T19:32:49.434815Z", + "iopub.status.busy": "2024-08-15T19:32:49.434559Z", + "iopub.status.idle": "2024-08-15T19:32:49.442077Z", + "shell.execute_reply": "2024-08-15T19:32:49.441625Z" } }, "outputs": [], @@ -1457,7 +1457,7 @@ }, { "cell_type": "markdown", - "id": "df33427d", + "id": "1e8f346c", "metadata": {}, "source": [ "The functions above collect sets of near-duplicate examples. Within each\n", @@ -1472,13 +1472,13 @@ { "cell_type": "code", "execution_count": 19, - "id": "442bf65a", + "id": "db1ab507", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:18.013746Z", - "iopub.status.busy": "2024-08-12T18:59:18.013327Z", - "iopub.status.idle": "2024-08-12T18:59:18.033961Z", - "shell.execute_reply": "2024-08-12T18:59:18.033341Z" + "iopub.execute_input": "2024-08-15T19:32:49.444206Z", + "iopub.status.busy": "2024-08-15T19:32:49.443885Z", + "iopub.status.idle": "2024-08-15T19:32:49.466030Z", + "shell.execute_reply": "2024-08-15T19:32:49.465456Z" } }, "outputs": [ @@ -1521,13 +1521,13 @@ { "cell_type": "code", "execution_count": 20, - "id": "8c4cf9b9", + "id": "497c6e0e", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:18.036179Z", - "iopub.status.busy": "2024-08-12T18:59:18.035977Z", - "iopub.status.idle": "2024-08-12T18:59:18.039688Z", - "shell.execute_reply": "2024-08-12T18:59:18.039180Z" + "iopub.execute_input": "2024-08-15T19:32:49.468364Z", + "iopub.status.busy": "2024-08-15T19:32:49.468163Z", + "iopub.status.idle": "2024-08-15T19:32:49.471663Z", + "shell.execute_reply": "2024-08-15T19:32:49.471107Z" } }, "outputs": [ @@ -1622,23 +1622,30 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - 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    6. Check for issues in training data and algorithmically correct them6. Check for issues in training data and algorithmically correct them

    Now instead of manually inspecting the detected issues in our training data, we will automatically filter all data points out of the training set that cleanlab has flagged as being likely mislabeled, outliers, or near duplicates. Unlike the test data which cannot be blindly auto-curated because we must ensure reliable model evaluation, the training data can be more aggressively modified as long as we’re able to faithfully evaluate the resulting fitted model.

    diff --git a/master/tutorials/improving_ml_performance.ipynb b/master/tutorials/improving_ml_performance.ipynb index 5a4b84c49..0ab6a96ae 100644 --- a/master/tutorials/improving_ml_performance.ipynb +++ b/master/tutorials/improving_ml_performance.ipynb @@ -60,10 +60,10 @@ "id": "2d638465", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:21.826268Z", - "iopub.status.busy": "2024-08-12T18:59:21.826079Z", - "iopub.status.idle": "2024-08-12T18:59:23.362509Z", - "shell.execute_reply": "2024-08-12T18:59:23.361803Z" + "iopub.execute_input": "2024-08-15T19:32:52.987835Z", + "iopub.status.busy": "2024-08-15T19:32:52.987664Z", + "iopub.status.idle": "2024-08-15T19:32:54.376429Z", + "shell.execute_reply": "2024-08-15T19:32:54.375879Z" }, "nbsphinx": "hidden" }, @@ -73,7 +73,7 @@ "dependencies = [\"cleanlab\", \"xgboost\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -99,10 +99,10 @@ "id": "b0bbf715-47c6-44ea-b15e-89800e62ee04", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:23.365369Z", - "iopub.status.busy": "2024-08-12T18:59:23.365034Z", - "iopub.status.idle": "2024-08-12T18:59:23.369094Z", - "shell.execute_reply": "2024-08-12T18:59:23.368592Z" + "iopub.execute_input": "2024-08-15T19:32:54.378936Z", + "iopub.status.busy": "2024-08-15T19:32:54.378500Z", + "iopub.status.idle": "2024-08-15T19:32:54.382201Z", + "shell.execute_reply": "2024-08-15T19:32:54.381641Z" } }, "outputs": [], @@ -140,10 +140,10 @@ "id": "c58f8015-d051-411c-9e03-5659cf3ad956", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:23.371289Z", - "iopub.status.busy": "2024-08-12T18:59:23.370919Z", - "iopub.status.idle": "2024-08-12T18:59:23.992532Z", - "shell.execute_reply": "2024-08-12T18:59:23.992005Z" + "iopub.execute_input": "2024-08-15T19:32:54.384231Z", + "iopub.status.busy": "2024-08-15T19:32:54.383929Z", + "iopub.status.idle": "2024-08-15T19:32:54.768880Z", + "shell.execute_reply": "2024-08-15T19:32:54.768326Z" } }, "outputs": [ @@ -273,10 +273,10 @@ "id": "1b5f50e6-d125-4e61-b63e-4004f0c9099a", "metadata": { "execution": { - 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"iopub.execute_input": "2024-08-12T18:59:24.011516Z", - "iopub.status.busy": "2024-08-12T18:59:24.011159Z", - "iopub.status.idle": "2024-08-12T18:59:24.015977Z", - "shell.execute_reply": "2024-08-12T18:59:24.015484Z" + "iopub.execute_input": "2024-08-15T19:32:54.787398Z", + "iopub.status.busy": "2024-08-15T19:32:54.787088Z", + "iopub.status.idle": "2024-08-15T19:32:54.791904Z", + "shell.execute_reply": "2024-08-15T19:32:54.791314Z" } }, "outputs": [], @@ -449,10 +449,10 @@ "id": "46275634-da56-4e58-9061-8108be2b585d", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.018166Z", - "iopub.status.busy": "2024-08-12T18:59:24.017823Z", - "iopub.status.idle": "2024-08-12T18:59:24.023580Z", - "shell.execute_reply": "2024-08-12T18:59:24.023107Z" + "iopub.execute_input": "2024-08-15T19:32:54.793915Z", + "iopub.status.busy": "2024-08-15T19:32:54.793578Z", + "iopub.status.idle": "2024-08-15T19:32:54.799184Z", + "shell.execute_reply": "2024-08-15T19:32:54.798512Z" } }, "outputs": [], @@ -488,10 +488,10 @@ "id": "769c4c5e-a7ff-4e02-bee5-2b2e676aec14", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.025655Z", - "iopub.status.busy": "2024-08-12T18:59:24.025309Z", - "iopub.status.idle": "2024-08-12T18:59:24.029614Z", - "shell.execute_reply": "2024-08-12T18:59:24.028928Z" + "iopub.execute_input": "2024-08-15T19:32:54.801571Z", + "iopub.status.busy": "2024-08-15T19:32:54.801171Z", + "iopub.status.idle": "2024-08-15T19:32:54.805430Z", + "shell.execute_reply": "2024-08-15T19:32:54.804946Z" } }, "outputs": [], @@ -506,10 +506,10 @@ "id": "7ac47c3d-9e87-45b7-9064-bfa45578872e", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.031973Z", - "iopub.status.busy": "2024-08-12T18:59:24.031689Z", - "iopub.status.idle": "2024-08-12T18:59:24.101331Z", - "shell.execute_reply": "2024-08-12T18:59:24.100635Z" + "iopub.execute_input": "2024-08-15T19:32:54.807369Z", + "iopub.status.busy": "2024-08-15T19:32:54.807038Z", + "iopub.status.idle": "2024-08-15T19:32:54.872265Z", + "shell.execute_reply": "2024-08-15T19:32:54.871648Z" } }, "outputs": [ @@ -609,10 +609,10 @@ "id": "6cef169e-d15b-4d18-9cb7-8ea589557e6b", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.104215Z", - "iopub.status.busy": "2024-08-12T18:59:24.103661Z", - "iopub.status.idle": "2024-08-12T18:59:24.114955Z", - "shell.execute_reply": "2024-08-12T18:59:24.114435Z" + "iopub.execute_input": "2024-08-15T19:32:54.874790Z", + "iopub.status.busy": "2024-08-15T19:32:54.874416Z", + "iopub.status.idle": "2024-08-15T19:32:54.885116Z", + "shell.execute_reply": "2024-08-15T19:32:54.884622Z" } }, "outputs": [ @@ -724,10 +724,10 @@ "id": "b68e0418-86cf-431f-9107-2dd0a310ca42", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.117518Z", - "iopub.status.busy": "2024-08-12T18:59:24.117223Z", - "iopub.status.idle": "2024-08-12T18:59:24.138341Z", - "shell.execute_reply": "2024-08-12T18:59:24.137783Z" + "iopub.execute_input": "2024-08-15T19:32:54.887504Z", + "iopub.status.busy": "2024-08-15T19:32:54.887130Z", + "iopub.status.idle": "2024-08-15T19:32:54.906419Z", + "shell.execute_reply": "2024-08-15T19:32:54.905933Z" } }, "outputs": [ @@ -931,10 +931,10 @@ "id": "0e9bd131-429f-48af-b4fc-ed8b907950b9", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.141061Z", - "iopub.status.busy": "2024-08-12T18:59:24.140659Z", - "iopub.status.idle": "2024-08-12T18:59:24.144913Z", - "shell.execute_reply": "2024-08-12T18:59:24.144417Z" + "iopub.execute_input": "2024-08-15T19:32:54.908724Z", + "iopub.status.busy": "2024-08-15T19:32:54.908352Z", + "iopub.status.idle": "2024-08-15T19:32:54.912259Z", + "shell.execute_reply": "2024-08-15T19:32:54.911781Z" } }, "outputs": [ @@ -968,10 +968,10 @@ "id": "e72320ec-7792-4347-b2fb-630f2519127c", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.147445Z", - "iopub.status.busy": "2024-08-12T18:59:24.147051Z", - "iopub.status.idle": "2024-08-12T18:59:24.151429Z", - "shell.execute_reply": "2024-08-12T18:59:24.150931Z" + "iopub.execute_input": "2024-08-15T19:32:54.914556Z", + "iopub.status.busy": "2024-08-15T19:32:54.914186Z", + "iopub.status.idle": "2024-08-15T19:32:54.918310Z", + "shell.execute_reply": "2024-08-15T19:32:54.917830Z" } }, "outputs": [ @@ -1005,10 +1005,10 @@ "id": "8520ba4a-3ad6-408a-b377-3f47c32d745a", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.154790Z", - "iopub.status.busy": "2024-08-12T18:59:24.153828Z", - "iopub.status.idle": "2024-08-12T18:59:24.165935Z", - "shell.execute_reply": "2024-08-12T18:59:24.165486Z" + "iopub.execute_input": "2024-08-15T19:32:54.920638Z", + "iopub.status.busy": "2024-08-15T19:32:54.920272Z", + "iopub.status.idle": "2024-08-15T19:32:54.931529Z", + "shell.execute_reply": "2024-08-15T19:32:54.931041Z" } }, "outputs": [ @@ -1205,10 +1205,10 @@ "id": "3c002665-c48b-4f04-91f7-ad112a49efc7", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.168518Z", - "iopub.status.busy": "2024-08-12T18:59:24.168008Z", - "iopub.status.idle": "2024-08-12T18:59:24.173279Z", - "shell.execute_reply": "2024-08-12T18:59:24.172745Z" + "iopub.execute_input": "2024-08-15T19:32:54.933722Z", + "iopub.status.busy": "2024-08-15T19:32:54.933424Z", + "iopub.status.idle": "2024-08-15T19:32:54.937226Z", + "shell.execute_reply": "2024-08-15T19:32:54.936834Z" } }, "outputs": [], @@ -1234,10 +1234,10 @@ "id": "36319f39-f563-4f63-913f-821373180350", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.175732Z", - "iopub.status.busy": "2024-08-12T18:59:24.175539Z", - "iopub.status.idle": "2024-08-12T18:59:24.290251Z", - "shell.execute_reply": "2024-08-12T18:59:24.289739Z" + "iopub.execute_input": "2024-08-15T19:32:54.939161Z", + "iopub.status.busy": "2024-08-15T19:32:54.938844Z", + "iopub.status.idle": "2024-08-15T19:32:55.050645Z", + "shell.execute_reply": "2024-08-15T19:32:55.050174Z" } }, "outputs": [ @@ -1711,10 +1711,10 @@ "id": "044c0eb1-299a-4851-b1bf-268d5bce56c1", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.292625Z", - "iopub.status.busy": "2024-08-12T18:59:24.292246Z", - "iopub.status.idle": "2024-08-12T18:59:24.298593Z", - "shell.execute_reply": "2024-08-12T18:59:24.298095Z" + "iopub.execute_input": "2024-08-15T19:32:55.052707Z", + "iopub.status.busy": "2024-08-15T19:32:55.052405Z", + "iopub.status.idle": "2024-08-15T19:32:55.057811Z", + "shell.execute_reply": "2024-08-15T19:32:55.057330Z" } }, "outputs": [], @@ -1738,10 +1738,10 @@ "id": "c43df278-abfe-40e5-9d48-2df3efea9379", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:24.301176Z", - "iopub.status.busy": "2024-08-12T18:59:24.300603Z", - "iopub.status.idle": "2024-08-12T18:59:26.626151Z", - "shell.execute_reply": "2024-08-12T18:59:26.625494Z" + "iopub.execute_input": "2024-08-15T19:32:55.060815Z", + "iopub.status.busy": "2024-08-15T19:32:55.059932Z", + "iopub.status.idle": "2024-08-15T19:32:57.154389Z", + "shell.execute_reply": "2024-08-15T19:32:57.153766Z" } }, "outputs": [ @@ -1953,10 +1953,10 @@ "id": "77c7f776-54b3-45b5-9207-715d6d2e90c0", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:26.629258Z", - "iopub.status.busy": "2024-08-12T18:59:26.628623Z", - "iopub.status.idle": "2024-08-12T18:59:26.642060Z", - "shell.execute_reply": "2024-08-12T18:59:26.641543Z" + "iopub.execute_input": "2024-08-15T19:32:57.158451Z", + "iopub.status.busy": "2024-08-15T19:32:57.157400Z", + "iopub.status.idle": "2024-08-15T19:32:57.172150Z", + "shell.execute_reply": "2024-08-15T19:32:57.171639Z" } }, "outputs": [ @@ -2073,10 +2073,10 @@ "id": "7e218d04-0729-4f42-b264-51c73601ebe6", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:26.644567Z", - "iopub.status.busy": "2024-08-12T18:59:26.644161Z", - "iopub.status.idle": "2024-08-12T18:59:26.647095Z", - "shell.execute_reply": "2024-08-12T18:59:26.646603Z" + "iopub.execute_input": "2024-08-15T19:32:57.175587Z", + "iopub.status.busy": "2024-08-15T19:32:57.174664Z", + "iopub.status.idle": "2024-08-15T19:32:57.178626Z", + "shell.execute_reply": "2024-08-15T19:32:57.178120Z" } }, "outputs": [], @@ -2090,10 +2090,10 @@ "id": "7e2bdb41-321e-4929-aa01-1f60948b9e8b", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:26.650162Z", - "iopub.status.busy": "2024-08-12T18:59:26.649219Z", - "iopub.status.idle": "2024-08-12T18:59:26.654885Z", - "shell.execute_reply": "2024-08-12T18:59:26.654380Z" + "iopub.execute_input": "2024-08-15T19:32:57.182037Z", + "iopub.status.busy": "2024-08-15T19:32:57.181135Z", + "iopub.status.idle": "2024-08-15T19:32:57.186622Z", + "shell.execute_reply": "2024-08-15T19:32:57.186123Z" } }, "outputs": [], @@ -2117,10 +2117,10 @@ "id": "5ce2d89f-e832-448d-bfac-9941da15c895", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:26.658482Z", - "iopub.status.busy": "2024-08-12T18:59:26.657542Z", - "iopub.status.idle": "2024-08-12T18:59:26.694816Z", - "shell.execute_reply": "2024-08-12T18:59:26.694252Z" + "iopub.execute_input": "2024-08-15T19:32:57.190032Z", + "iopub.status.busy": "2024-08-15T19:32:57.189130Z", + "iopub.status.idle": "2024-08-15T19:32:57.221753Z", + "shell.execute_reply": "2024-08-15T19:32:57.221244Z" } }, "outputs": [ @@ -2160,10 +2160,10 @@ "id": "9f437756-112e-4531-84fc-6ceadd0c9ef5", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:26.697458Z", - "iopub.status.busy": "2024-08-12T18:59:26.697065Z", - "iopub.status.idle": "2024-08-12T18:59:27.254855Z", - "shell.execute_reply": "2024-08-12T18:59:27.254284Z" + "iopub.execute_input": "2024-08-15T19:32:57.224656Z", + "iopub.status.busy": "2024-08-15T19:32:57.223974Z", + "iopub.status.idle": "2024-08-15T19:32:57.753860Z", + "shell.execute_reply": "2024-08-15T19:32:57.753315Z" } }, "outputs": [], @@ -2194,10 +2194,10 @@ "id": "707625f6", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.257761Z", - "iopub.status.busy": "2024-08-12T18:59:27.257381Z", - "iopub.status.idle": "2024-08-12T18:59:27.403783Z", - "shell.execute_reply": "2024-08-12T18:59:27.403129Z" + "iopub.execute_input": "2024-08-15T19:32:57.757597Z", + "iopub.status.busy": "2024-08-15T19:32:57.756664Z", + "iopub.status.idle": "2024-08-15T19:32:57.893127Z", + "shell.execute_reply": "2024-08-15T19:32:57.892444Z" } }, "outputs": [ @@ -2231,7 +2231,7 @@ " null 1.000000 0\n", " non_iid 0.437267 0\n", " class_imbalance 0.146423 0\n", - "underperforming_group 0.978605 0\n", + "underperforming_group 0.977223 0\n", "\n", "(Note: A lower score indicates a more severe issue across all examples in the dataset.)\n", "\n", @@ -2374,15 +2374,15 @@ " \n", "\n", "Number of examples with this issue: 0\n", - "Overall dataset quality in terms of this issue: 0.9786\n", + "Overall dataset quality in terms of this issue: 0.9772\n", "\n", "Examples representing most severe instances of this issue:\n", " is_underperforming_group_issue underperforming_group_score\n", - "0 False 1.0\n", - "396 False 1.0\n", - "397 False 1.0\n", - "398 False 1.0\n", - "399 False 1.0\n" + "0 False 0.977223\n", + "402 False 0.977223\n", + "401 False 0.977223\n", + "400 False 0.977223\n", + "399 False 0.977223\n" ] } ], @@ -2408,10 +2408,10 @@ "id": "25afe46c-a521-483c-b168-728c76d970dc", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.407718Z", - "iopub.status.busy": "2024-08-12T18:59:27.406705Z", - "iopub.status.idle": "2024-08-12T18:59:27.416124Z", - "shell.execute_reply": "2024-08-12T18:59:27.415579Z" + "iopub.execute_input": "2024-08-15T19:32:57.895972Z", + "iopub.status.busy": "2024-08-15T19:32:57.895536Z", + "iopub.status.idle": "2024-08-15T19:32:57.902656Z", + "shell.execute_reply": "2024-08-15T19:32:57.902135Z" } }, "outputs": [ @@ -2441,10 +2441,10 @@ "id": "6efcf06f-cc40-4964-87df-5204d3b1b9d4", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.419912Z", - "iopub.status.busy": "2024-08-12T18:59:27.418954Z", - "iopub.status.idle": "2024-08-12T18:59:27.427553Z", - "shell.execute_reply": "2024-08-12T18:59:27.427031Z" + "iopub.execute_input": "2024-08-15T19:32:57.904923Z", + "iopub.status.busy": "2024-08-15T19:32:57.904570Z", + "iopub.status.idle": "2024-08-15T19:32:57.910759Z", + "shell.execute_reply": "2024-08-15T19:32:57.910246Z" } }, "outputs": [ @@ -2477,10 +2477,10 @@ "id": "7bc87d72-bbd5-4ed2-bc38-2218862ddfbd", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.431276Z", - "iopub.status.busy": "2024-08-12T18:59:27.430306Z", - "iopub.status.idle": "2024-08-12T18:59:27.438426Z", - "shell.execute_reply": "2024-08-12T18:59:27.437887Z" + "iopub.execute_input": "2024-08-15T19:32:57.912949Z", + "iopub.status.busy": "2024-08-15T19:32:57.912608Z", + "iopub.status.idle": "2024-08-15T19:32:57.918113Z", + "shell.execute_reply": "2024-08-15T19:32:57.917588Z" } }, "outputs": [ @@ -2513,10 +2513,10 @@ "id": "9c70be3e-0ba2-4e3e-8c50-359d402ca1fe", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.442229Z", - "iopub.status.busy": "2024-08-12T18:59:27.441274Z", - "iopub.status.idle": "2024-08-12T18:59:27.446605Z", - "shell.execute_reply": "2024-08-12T18:59:27.445954Z" + "iopub.execute_input": "2024-08-15T19:32:57.920897Z", + "iopub.status.busy": "2024-08-15T19:32:57.920430Z", + "iopub.status.idle": "2024-08-15T19:32:57.924900Z", + "shell.execute_reply": "2024-08-15T19:32:57.924385Z" } }, "outputs": [ @@ -2542,10 +2542,10 @@ "id": "08080458-0cd7-447d-80e6-384cb8d31eaf", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.448859Z", - "iopub.status.busy": "2024-08-12T18:59:27.448667Z", - "iopub.status.idle": "2024-08-12T18:59:27.454140Z", - "shell.execute_reply": "2024-08-12T18:59:27.453686Z" + "iopub.execute_input": "2024-08-15T19:32:57.927679Z", + "iopub.status.busy": "2024-08-15T19:32:57.927202Z", + "iopub.status.idle": "2024-08-15T19:32:57.932198Z", + "shell.execute_reply": "2024-08-15T19:32:57.931697Z" } }, "outputs": [], @@ -2569,10 +2569,10 @@ "id": "009bb215-4d26-47da-a230-d0ccf4122629", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.456194Z", - "iopub.status.busy": "2024-08-12T18:59:27.456000Z", - "iopub.status.idle": "2024-08-12T18:59:27.537799Z", - "shell.execute_reply": "2024-08-12T18:59:27.537248Z" + "iopub.execute_input": "2024-08-15T19:32:57.934623Z", + "iopub.status.busy": "2024-08-15T19:32:57.934275Z", + "iopub.status.idle": "2024-08-15T19:32:58.013729Z", + "shell.execute_reply": "2024-08-15T19:32:58.013188Z" } }, "outputs": [ @@ -3052,10 +3052,10 @@ "id": "dcaeda51-9b24-4c04-889d-7e63563594fc", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.540099Z", - "iopub.status.busy": "2024-08-12T18:59:27.539886Z", - "iopub.status.idle": "2024-08-12T18:59:27.554683Z", - "shell.execute_reply": "2024-08-12T18:59:27.553987Z" + "iopub.execute_input": "2024-08-15T19:32:58.017160Z", + "iopub.status.busy": "2024-08-15T19:32:58.016821Z", + "iopub.status.idle": "2024-08-15T19:32:58.028876Z", + "shell.execute_reply": "2024-08-15T19:32:58.028390Z" } }, "outputs": [ @@ -3111,10 +3111,10 @@ "id": "1d92d78d-e4a8-4322-bf38-f5a5dae3bf17", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.557753Z", - "iopub.status.busy": "2024-08-12T18:59:27.557171Z", - "iopub.status.idle": "2024-08-12T18:59:27.560724Z", - "shell.execute_reply": "2024-08-12T18:59:27.560114Z" + "iopub.execute_input": "2024-08-15T19:32:58.031728Z", + "iopub.status.busy": "2024-08-15T19:32:58.031238Z", + "iopub.status.idle": "2024-08-15T19:32:58.034186Z", + "shell.execute_reply": "2024-08-15T19:32:58.033784Z" } }, "outputs": [], @@ -3150,10 +3150,10 @@ "id": "941ab2a6", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.562976Z", - "iopub.status.busy": "2024-08-12T18:59:27.562789Z", - "iopub.status.idle": "2024-08-12T18:59:27.573678Z", - "shell.execute_reply": "2024-08-12T18:59:27.573001Z" + "iopub.execute_input": "2024-08-15T19:32:58.036237Z", + "iopub.status.busy": "2024-08-15T19:32:58.035919Z", + "iopub.status.idle": "2024-08-15T19:32:58.044828Z", + "shell.execute_reply": "2024-08-15T19:32:58.044388Z" } }, "outputs": [], @@ -3261,10 +3261,10 @@ "id": "50666fb9", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.576419Z", - "iopub.status.busy": "2024-08-12T18:59:27.576012Z", - "iopub.status.idle": "2024-08-12T18:59:27.582946Z", - "shell.execute_reply": "2024-08-12T18:59:27.582421Z" + "iopub.execute_input": "2024-08-15T19:32:58.046882Z", + "iopub.status.busy": "2024-08-15T19:32:58.046533Z", + "iopub.status.idle": "2024-08-15T19:32:58.052921Z", + "shell.execute_reply": "2024-08-15T19:32:58.052471Z" }, "nbsphinx": "hidden" }, @@ -3346,10 +3346,10 @@ "id": "f5aa2883-d20d-481f-a012-fcc7ff8e3e7e", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.585144Z", - "iopub.status.busy": "2024-08-12T18:59:27.584831Z", - "iopub.status.idle": "2024-08-12T18:59:27.588435Z", - "shell.execute_reply": "2024-08-12T18:59:27.587844Z" + "iopub.execute_input": "2024-08-15T19:32:58.054841Z", + "iopub.status.busy": "2024-08-15T19:32:58.054509Z", + "iopub.status.idle": "2024-08-15T19:32:58.057614Z", + "shell.execute_reply": "2024-08-15T19:32:58.057181Z" } }, "outputs": [], @@ -3373,10 +3373,10 @@ "id": "ce1c0ada-88b1-4654-b43f-3c0b59002979", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:27.590688Z", - "iopub.status.busy": "2024-08-12T18:59:27.590349Z", - "iopub.status.idle": "2024-08-12T18:59:31.669748Z", - "shell.execute_reply": "2024-08-12T18:59:31.669230Z" + "iopub.execute_input": "2024-08-15T19:32:58.059553Z", + "iopub.status.busy": "2024-08-15T19:32:58.059224Z", + "iopub.status.idle": "2024-08-15T19:33:02.036453Z", + "shell.execute_reply": "2024-08-15T19:33:02.035935Z" } }, "outputs": [ @@ -3419,10 +3419,10 @@ "id": "3f572acf-31c3-4874-9100-451796e35b06", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:31.672207Z", - "iopub.status.busy": "2024-08-12T18:59:31.671838Z", - "iopub.status.idle": "2024-08-12T18:59:31.675032Z", - "shell.execute_reply": "2024-08-12T18:59:31.674603Z" + "iopub.execute_input": "2024-08-15T19:33:02.038836Z", + "iopub.status.busy": "2024-08-15T19:33:02.038499Z", + "iopub.status.idle": "2024-08-15T19:33:02.041550Z", + "shell.execute_reply": "2024-08-15T19:33:02.041156Z" } }, "outputs": [ @@ -3460,10 +3460,10 @@ "id": "6a025a88", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:31.677196Z", - "iopub.status.busy": "2024-08-12T18:59:31.676887Z", - "iopub.status.idle": "2024-08-12T18:59:31.679964Z", - "shell.execute_reply": "2024-08-12T18:59:31.679566Z" + "iopub.execute_input": "2024-08-15T19:33:02.043874Z", + "iopub.status.busy": "2024-08-15T19:33:02.043364Z", + "iopub.status.idle": "2024-08-15T19:33:02.046983Z", + "shell.execute_reply": "2024-08-15T19:33:02.046525Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/indepth_overview.ipynb b/master/tutorials/indepth_overview.ipynb index 9eab66f97..45a1e424f 100644 --- a/master/tutorials/indepth_overview.ipynb +++ b/master/tutorials/indepth_overview.ipynb @@ -53,10 +53,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:35.304974Z", - "iopub.status.busy": "2024-08-12T18:59:35.304798Z", - "iopub.status.idle": "2024-08-12T18:59:36.757045Z", - "shell.execute_reply": "2024-08-12T18:59:36.756394Z" + "iopub.execute_input": "2024-08-15T19:33:05.249152Z", + "iopub.status.busy": "2024-08-15T19:33:05.248732Z", + "iopub.status.idle": "2024-08-15T19:33:06.624950Z", + "shell.execute_reply": "2024-08-15T19:33:06.624404Z" }, "nbsphinx": "hidden" }, @@ -68,7 +68,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -95,10 +95,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:36.759809Z", - "iopub.status.busy": "2024-08-12T18:59:36.759444Z", - "iopub.status.idle": "2024-08-12T18:59:36.763080Z", - "shell.execute_reply": "2024-08-12T18:59:36.762530Z" + "iopub.execute_input": "2024-08-15T19:33:06.627498Z", + "iopub.status.busy": "2024-08-15T19:33:06.627050Z", + "iopub.status.idle": "2024-08-15T19:33:06.630342Z", + "shell.execute_reply": "2024-08-15T19:33:06.629890Z" }, "id": "avXlHJcXjruP" }, @@ -234,10 +234,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:36.765342Z", - "iopub.status.busy": "2024-08-12T18:59:36.764890Z", - "iopub.status.idle": "2024-08-12T18:59:36.776716Z", - "shell.execute_reply": "2024-08-12T18:59:36.776099Z" + "iopub.execute_input": "2024-08-15T19:33:06.632428Z", + "iopub.status.busy": "2024-08-15T19:33:06.632092Z", + "iopub.status.idle": "2024-08-15T19:33:06.643402Z", + "shell.execute_reply": "2024-08-15T19:33:06.642989Z" }, "nbsphinx": "hidden" }, @@ -340,10 +340,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:36.779257Z", - "iopub.status.busy": "2024-08-12T18:59:36.778841Z", - "iopub.status.idle": "2024-08-12T18:59:36.993253Z", - "shell.execute_reply": "2024-08-12T18:59:36.992612Z" + "iopub.execute_input": "2024-08-15T19:33:06.645477Z", + "iopub.status.busy": "2024-08-15T19:33:06.645146Z", + "iopub.status.idle": "2024-08-15T19:33:06.857292Z", + "shell.execute_reply": "2024-08-15T19:33:06.856683Z" } }, "outputs": [ @@ -393,10 +393,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:36.995645Z", - "iopub.status.busy": "2024-08-12T18:59:36.995301Z", - "iopub.status.idle": "2024-08-12T18:59:37.022394Z", - "shell.execute_reply": "2024-08-12T18:59:37.021879Z" + "iopub.execute_input": "2024-08-15T19:33:06.859623Z", + "iopub.status.busy": "2024-08-15T19:33:06.859348Z", + "iopub.status.idle": "2024-08-15T19:33:06.885754Z", + "shell.execute_reply": "2024-08-15T19:33:06.885315Z" } }, "outputs": [], @@ -428,10 +428,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:37.025051Z", - "iopub.status.busy": "2024-08-12T18:59:37.024560Z", - "iopub.status.idle": "2024-08-12T18:59:39.262272Z", - "shell.execute_reply": "2024-08-12T18:59:39.261549Z" + "iopub.execute_input": "2024-08-15T19:33:06.887779Z", + "iopub.status.busy": "2024-08-15T19:33:06.887439Z", + "iopub.status.idle": "2024-08-15T19:33:08.964603Z", + "shell.execute_reply": "2024-08-15T19:33:08.963955Z" } }, "outputs": [ @@ -474,10 +474,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:39.265033Z", - "iopub.status.busy": "2024-08-12T18:59:39.264285Z", - "iopub.status.idle": "2024-08-12T18:59:39.282778Z", - "shell.execute_reply": "2024-08-12T18:59:39.282196Z" + "iopub.execute_input": "2024-08-15T19:33:08.966928Z", + "iopub.status.busy": "2024-08-15T19:33:08.966590Z", + "iopub.status.idle": "2024-08-15T19:33:08.984980Z", + "shell.execute_reply": "2024-08-15T19:33:08.984412Z" }, "scrolled": true }, @@ -607,10 +607,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:39.285167Z", - "iopub.status.busy": "2024-08-12T18:59:39.284691Z", - "iopub.status.idle": "2024-08-12T18:59:40.937315Z", - "shell.execute_reply": "2024-08-12T18:59:40.936613Z" + "iopub.execute_input": "2024-08-15T19:33:08.987063Z", + "iopub.status.busy": "2024-08-15T19:33:08.986722Z", + "iopub.status.idle": "2024-08-15T19:33:10.546083Z", + "shell.execute_reply": "2024-08-15T19:33:10.545493Z" }, "id": "AaHC5MRKjruT" }, @@ -729,10 +729,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:40.940438Z", - "iopub.status.busy": "2024-08-12T18:59:40.939654Z", - "iopub.status.idle": "2024-08-12T18:59:40.954542Z", - "shell.execute_reply": "2024-08-12T18:59:40.953980Z" + "iopub.execute_input": "2024-08-15T19:33:10.548990Z", + "iopub.status.busy": "2024-08-15T19:33:10.548171Z", + "iopub.status.idle": "2024-08-15T19:33:10.561779Z", + "shell.execute_reply": "2024-08-15T19:33:10.561238Z" }, "id": "Wy27rvyhjruU" }, @@ -781,10 +781,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:40.956770Z", - "iopub.status.busy": "2024-08-12T18:59:40.956575Z", - "iopub.status.idle": "2024-08-12T18:59:41.043940Z", - "shell.execute_reply": "2024-08-12T18:59:41.043268Z" + "iopub.execute_input": "2024-08-15T19:33:10.563997Z", + "iopub.status.busy": "2024-08-15T19:33:10.563694Z", + "iopub.status.idle": "2024-08-15T19:33:10.642956Z", + "shell.execute_reply": "2024-08-15T19:33:10.642292Z" }, "id": "Db8YHnyVjruU" }, @@ -891,10 +891,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.046625Z", - "iopub.status.busy": "2024-08-12T18:59:41.046255Z", - "iopub.status.idle": "2024-08-12T18:59:41.261565Z", - "shell.execute_reply": "2024-08-12T18:59:41.260957Z" + "iopub.execute_input": "2024-08-15T19:33:10.645297Z", + "iopub.status.busy": "2024-08-15T19:33:10.644936Z", + "iopub.status.idle": "2024-08-15T19:33:10.858056Z", + "shell.execute_reply": "2024-08-15T19:33:10.857455Z" }, "id": "iJqAHuS2jruV" }, @@ -931,10 +931,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.264074Z", - "iopub.status.busy": "2024-08-12T18:59:41.263645Z", - "iopub.status.idle": "2024-08-12T18:59:41.282286Z", - "shell.execute_reply": "2024-08-12T18:59:41.281805Z" + "iopub.execute_input": "2024-08-15T19:33:10.860261Z", + "iopub.status.busy": "2024-08-15T19:33:10.859901Z", + "iopub.status.idle": "2024-08-15T19:33:10.876572Z", + "shell.execute_reply": "2024-08-15T19:33:10.876119Z" }, "id": "PcPTZ_JJG3Cx" }, @@ -1400,10 +1400,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.284554Z", - "iopub.status.busy": "2024-08-12T18:59:41.284169Z", - "iopub.status.idle": "2024-08-12T18:59:41.293947Z", - "shell.execute_reply": "2024-08-12T18:59:41.293461Z" + "iopub.execute_input": "2024-08-15T19:33:10.878719Z", + "iopub.status.busy": "2024-08-15T19:33:10.878387Z", + "iopub.status.idle": "2024-08-15T19:33:10.887970Z", + "shell.execute_reply": "2024-08-15T19:33:10.887477Z" }, "id": "0lonvOYvjruV" }, @@ -1550,10 +1550,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.296255Z", - "iopub.status.busy": "2024-08-12T18:59:41.295902Z", - "iopub.status.idle": "2024-08-12T18:59:41.393592Z", - "shell.execute_reply": "2024-08-12T18:59:41.392998Z" + "iopub.execute_input": "2024-08-15T19:33:10.890117Z", + "iopub.status.busy": "2024-08-15T19:33:10.889908Z", + "iopub.status.idle": "2024-08-15T19:33:10.981069Z", + "shell.execute_reply": "2024-08-15T19:33:10.980447Z" }, "id": "MfqTCa3kjruV" }, @@ -1634,10 +1634,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.396125Z", - "iopub.status.busy": "2024-08-12T18:59:41.395728Z", - "iopub.status.idle": "2024-08-12T18:59:41.553831Z", - "shell.execute_reply": "2024-08-12T18:59:41.553173Z" + "iopub.execute_input": "2024-08-15T19:33:10.983654Z", + "iopub.status.busy": "2024-08-15T19:33:10.983271Z", + "iopub.status.idle": "2024-08-15T19:33:11.121095Z", + "shell.execute_reply": "2024-08-15T19:33:11.120451Z" }, "id": "9ZtWAYXqMAPL" }, @@ -1697,10 +1697,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.556448Z", - "iopub.status.busy": "2024-08-12T18:59:41.556095Z", - "iopub.status.idle": "2024-08-12T18:59:41.560097Z", - "shell.execute_reply": "2024-08-12T18:59:41.559551Z" + "iopub.execute_input": "2024-08-15T19:33:11.123539Z", + "iopub.status.busy": "2024-08-15T19:33:11.123211Z", + "iopub.status.idle": "2024-08-15T19:33:11.127033Z", + "shell.execute_reply": "2024-08-15T19:33:11.126475Z" }, "id": "0rXP3ZPWjruW" }, @@ -1738,10 +1738,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.562409Z", - "iopub.status.busy": "2024-08-12T18:59:41.562052Z", - "iopub.status.idle": "2024-08-12T18:59:41.565967Z", - "shell.execute_reply": "2024-08-12T18:59:41.565404Z" + "iopub.execute_input": "2024-08-15T19:33:11.129102Z", + "iopub.status.busy": "2024-08-15T19:33:11.128770Z", + "iopub.status.idle": "2024-08-15T19:33:11.132416Z", + "shell.execute_reply": "2024-08-15T19:33:11.131874Z" }, "id": "-iRPe8KXjruW" }, @@ -1796,10 +1796,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.568132Z", - "iopub.status.busy": "2024-08-12T18:59:41.567785Z", - "iopub.status.idle": "2024-08-12T18:59:41.606435Z", - "shell.execute_reply": "2024-08-12T18:59:41.605862Z" + "iopub.execute_input": "2024-08-15T19:33:11.134323Z", + "iopub.status.busy": "2024-08-15T19:33:11.134052Z", + "iopub.status.idle": "2024-08-15T19:33:11.170810Z", + "shell.execute_reply": "2024-08-15T19:33:11.170234Z" }, "id": "ZpipUliyjruW" }, @@ -1850,10 +1850,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.608980Z", - "iopub.status.busy": "2024-08-12T18:59:41.608519Z", - "iopub.status.idle": "2024-08-12T18:59:41.650825Z", - "shell.execute_reply": "2024-08-12T18:59:41.650241Z" + "iopub.execute_input": "2024-08-15T19:33:11.173277Z", + "iopub.status.busy": "2024-08-15T19:33:11.172705Z", + "iopub.status.idle": "2024-08-15T19:33:11.213291Z", + "shell.execute_reply": "2024-08-15T19:33:11.212850Z" }, "id": "SLq-3q4xjruX" }, @@ -1922,10 +1922,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.653201Z", - "iopub.status.busy": "2024-08-12T18:59:41.652768Z", - "iopub.status.idle": "2024-08-12T18:59:41.758338Z", - "shell.execute_reply": "2024-08-12T18:59:41.757712Z" + "iopub.execute_input": "2024-08-15T19:33:11.215152Z", + "iopub.status.busy": "2024-08-15T19:33:11.214976Z", + "iopub.status.idle": "2024-08-15T19:33:11.316926Z", + "shell.execute_reply": "2024-08-15T19:33:11.316332Z" }, "id": "g5LHhhuqFbXK" }, @@ -1957,10 +1957,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.761298Z", - "iopub.status.busy": "2024-08-12T18:59:41.760816Z", - "iopub.status.idle": "2024-08-12T18:59:41.886836Z", - "shell.execute_reply": "2024-08-12T18:59:41.886199Z" + "iopub.execute_input": "2024-08-15T19:33:11.319579Z", + "iopub.status.busy": "2024-08-15T19:33:11.319191Z", + "iopub.status.idle": "2024-08-15T19:33:11.422280Z", + "shell.execute_reply": "2024-08-15T19:33:11.421643Z" }, "id": "p7w8F8ezBcet" }, @@ -2017,10 +2017,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:41.889204Z", - "iopub.status.busy": "2024-08-12T18:59:41.888953Z", - "iopub.status.idle": "2024-08-12T18:59:42.106786Z", - "shell.execute_reply": "2024-08-12T18:59:42.106237Z" + "iopub.execute_input": "2024-08-15T19:33:11.424721Z", + "iopub.status.busy": "2024-08-15T19:33:11.424339Z", + "iopub.status.idle": "2024-08-15T19:33:11.633366Z", + "shell.execute_reply": "2024-08-15T19:33:11.632876Z" }, "id": "WETRL74tE_sU" }, @@ -2055,10 +2055,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:42.109159Z", - "iopub.status.busy": "2024-08-12T18:59:42.108706Z", - "iopub.status.idle": "2024-08-12T18:59:42.343381Z", - "shell.execute_reply": "2024-08-12T18:59:42.342735Z" + "iopub.execute_input": "2024-08-15T19:33:11.635533Z", + "iopub.status.busy": "2024-08-15T19:33:11.635197Z", + "iopub.status.idle": "2024-08-15T19:33:11.849731Z", + "shell.execute_reply": "2024-08-15T19:33:11.849063Z" }, "id": "kCfdx2gOLmXS" }, @@ -2220,10 +2220,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:42.345991Z", - "iopub.status.busy": "2024-08-12T18:59:42.345741Z", - "iopub.status.idle": "2024-08-12T18:59:42.352404Z", - "shell.execute_reply": "2024-08-12T18:59:42.351909Z" + "iopub.execute_input": "2024-08-15T19:33:11.852026Z", + "iopub.status.busy": "2024-08-15T19:33:11.851822Z", + "iopub.status.idle": "2024-08-15T19:33:11.858036Z", + "shell.execute_reply": "2024-08-15T19:33:11.857595Z" }, "id": "-uogYRWFYnuu" }, @@ -2277,10 +2277,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:42.354511Z", - "iopub.status.busy": "2024-08-12T18:59:42.354162Z", - "iopub.status.idle": "2024-08-12T18:59:42.575035Z", - "shell.execute_reply": "2024-08-12T18:59:42.574431Z" + "iopub.execute_input": "2024-08-15T19:33:11.860119Z", + "iopub.status.busy": "2024-08-15T19:33:11.859783Z", + "iopub.status.idle": "2024-08-15T19:33:12.079969Z", + "shell.execute_reply": "2024-08-15T19:33:12.079382Z" }, "id": "pG-ljrmcYp9Q" }, @@ -2327,10 +2327,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:42.577426Z", - "iopub.status.busy": "2024-08-12T18:59:42.577078Z", - "iopub.status.idle": "2024-08-12T18:59:43.656887Z", - "shell.execute_reply": "2024-08-12T18:59:43.656289Z" + "iopub.execute_input": "2024-08-15T19:33:12.082273Z", + "iopub.status.busy": "2024-08-15T19:33:12.081911Z", + "iopub.status.idle": "2024-08-15T19:33:13.147784Z", + "shell.execute_reply": "2024-08-15T19:33:13.147235Z" }, "id": "wL3ngCnuLEWd" }, diff --git a/master/tutorials/multiannotator.ipynb b/master/tutorials/multiannotator.ipynb index 1b995e101..70a488552 100644 --- a/master/tutorials/multiannotator.ipynb +++ b/master/tutorials/multiannotator.ipynb @@ -88,10 +88,10 @@ "id": "a3ddc95f", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:47.417596Z", - "iopub.status.busy": "2024-08-12T18:59:47.417079Z", - "iopub.status.idle": "2024-08-12T18:59:48.878644Z", - "shell.execute_reply": "2024-08-12T18:59:48.878070Z" + "iopub.execute_input": "2024-08-15T19:33:17.597518Z", + "iopub.status.busy": "2024-08-15T19:33:17.597351Z", + "iopub.status.idle": "2024-08-15T19:33:19.041154Z", + "shell.execute_reply": "2024-08-15T19:33:19.040602Z" }, "nbsphinx": "hidden" }, @@ -101,7 +101,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -135,10 +135,10 @@ "id": "c4efd119", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:48.881128Z", - "iopub.status.busy": "2024-08-12T18:59:48.880825Z", - "iopub.status.idle": "2024-08-12T18:59:48.883983Z", - "shell.execute_reply": "2024-08-12T18:59:48.883519Z" + "iopub.execute_input": "2024-08-15T19:33:19.043853Z", + "iopub.status.busy": "2024-08-15T19:33:19.043472Z", + "iopub.status.idle": "2024-08-15T19:33:19.046747Z", + "shell.execute_reply": "2024-08-15T19:33:19.046283Z" } }, "outputs": [], @@ -263,10 +263,10 @@ "id": "c37c0a69", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:48.886113Z", - "iopub.status.busy": "2024-08-12T18:59:48.885774Z", - "iopub.status.idle": "2024-08-12T18:59:48.893491Z", - "shell.execute_reply": "2024-08-12T18:59:48.893014Z" + "iopub.execute_input": "2024-08-15T19:33:19.048737Z", + "iopub.status.busy": "2024-08-15T19:33:19.048563Z", + "iopub.status.idle": "2024-08-15T19:33:19.056920Z", + "shell.execute_reply": "2024-08-15T19:33:19.056373Z" }, "nbsphinx": "hidden" }, @@ -350,10 +350,10 @@ "id": "99f69523", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:48.895624Z", - "iopub.status.busy": "2024-08-12T18:59:48.895212Z", - "iopub.status.idle": "2024-08-12T18:59:48.944247Z", - "shell.execute_reply": "2024-08-12T18:59:48.943678Z" + "iopub.execute_input": "2024-08-15T19:33:19.058751Z", + "iopub.status.busy": "2024-08-15T19:33:19.058576Z", + "iopub.status.idle": "2024-08-15T19:33:19.107012Z", + "shell.execute_reply": "2024-08-15T19:33:19.106508Z" } }, "outputs": [], @@ -379,10 +379,10 @@ "id": "8f241c16", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:48.946974Z", - "iopub.status.busy": "2024-08-12T18:59:48.946526Z", - "iopub.status.idle": "2024-08-12T18:59:48.963914Z", - "shell.execute_reply": "2024-08-12T18:59:48.963313Z" + "iopub.execute_input": "2024-08-15T19:33:19.109507Z", + "iopub.status.busy": "2024-08-15T19:33:19.109153Z", + "iopub.status.idle": "2024-08-15T19:33:19.125576Z", + "shell.execute_reply": "2024-08-15T19:33:19.125139Z" } }, "outputs": [ @@ -597,10 +597,10 @@ "id": "4f0819ba", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:48.966276Z", - "iopub.status.busy": "2024-08-12T18:59:48.965835Z", - "iopub.status.idle": "2024-08-12T18:59:48.969991Z", - "shell.execute_reply": "2024-08-12T18:59:48.969454Z" + "iopub.execute_input": "2024-08-15T19:33:19.127677Z", + "iopub.status.busy": "2024-08-15T19:33:19.127253Z", + "iopub.status.idle": "2024-08-15T19:33:19.130978Z", + "shell.execute_reply": "2024-08-15T19:33:19.130525Z" } }, "outputs": [ @@ -671,10 +671,10 @@ "id": "d009f347", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:48.972099Z", - "iopub.status.busy": "2024-08-12T18:59:48.971921Z", - "iopub.status.idle": "2024-08-12T18:59:48.989790Z", - "shell.execute_reply": "2024-08-12T18:59:48.989320Z" + "iopub.execute_input": "2024-08-15T19:33:19.133034Z", + "iopub.status.busy": "2024-08-15T19:33:19.132859Z", + "iopub.status.idle": "2024-08-15T19:33:19.146529Z", + "shell.execute_reply": "2024-08-15T19:33:19.146084Z" } }, "outputs": [], @@ -698,10 +698,10 @@ "id": "cbd1e415", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:48.992099Z", - "iopub.status.busy": "2024-08-12T18:59:48.991748Z", - "iopub.status.idle": "2024-08-12T18:59:49.018554Z", - "shell.execute_reply": "2024-08-12T18:59:49.018031Z" + "iopub.execute_input": "2024-08-15T19:33:19.148616Z", + "iopub.status.busy": "2024-08-15T19:33:19.148301Z", + "iopub.status.idle": "2024-08-15T19:33:19.174266Z", + "shell.execute_reply": "2024-08-15T19:33:19.173701Z" } }, "outputs": [], @@ -738,10 +738,10 @@ "id": "6ca92617", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:49.021208Z", - "iopub.status.busy": "2024-08-12T18:59:49.020835Z", - "iopub.status.idle": "2024-08-12T18:59:51.271455Z", - "shell.execute_reply": "2024-08-12T18:59:51.270767Z" + "iopub.execute_input": "2024-08-15T19:33:19.176552Z", + "iopub.status.busy": "2024-08-15T19:33:19.176156Z", + "iopub.status.idle": "2024-08-15T19:33:21.295171Z", + "shell.execute_reply": "2024-08-15T19:33:21.294603Z" } }, "outputs": [], @@ -771,10 +771,10 @@ "id": "bf945113", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.274510Z", - "iopub.status.busy": "2024-08-12T18:59:51.273875Z", - "iopub.status.idle": "2024-08-12T18:59:51.281259Z", - "shell.execute_reply": "2024-08-12T18:59:51.280795Z" + "iopub.execute_input": "2024-08-15T19:33:21.297819Z", + "iopub.status.busy": "2024-08-15T19:33:21.297423Z", + "iopub.status.idle": "2024-08-15T19:33:21.304249Z", + "shell.execute_reply": "2024-08-15T19:33:21.303702Z" }, "scrolled": true }, @@ -885,10 +885,10 @@ "id": "14251ee0", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.283421Z", - "iopub.status.busy": "2024-08-12T18:59:51.283094Z", - "iopub.status.idle": "2024-08-12T18:59:51.295523Z", - "shell.execute_reply": "2024-08-12T18:59:51.294970Z" + "iopub.execute_input": "2024-08-15T19:33:21.306192Z", + "iopub.status.busy": "2024-08-15T19:33:21.305896Z", + "iopub.status.idle": "2024-08-15T19:33:21.318068Z", + "shell.execute_reply": "2024-08-15T19:33:21.317511Z" } }, "outputs": [ @@ -1138,10 +1138,10 @@ "id": "efe16638", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.297742Z", - "iopub.status.busy": "2024-08-12T18:59:51.297424Z", - "iopub.status.idle": "2024-08-12T18:59:51.304426Z", - "shell.execute_reply": "2024-08-12T18:59:51.303921Z" + "iopub.execute_input": "2024-08-15T19:33:21.320287Z", + "iopub.status.busy": "2024-08-15T19:33:21.319892Z", + "iopub.status.idle": "2024-08-15T19:33:21.326183Z", + "shell.execute_reply": "2024-08-15T19:33:21.325636Z" }, "scrolled": true }, @@ -1315,10 +1315,10 @@ "id": "abd0fb0b", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.306560Z", - "iopub.status.busy": "2024-08-12T18:59:51.306375Z", - "iopub.status.idle": "2024-08-12T18:59:51.308977Z", - "shell.execute_reply": "2024-08-12T18:59:51.308522Z" + "iopub.execute_input": "2024-08-15T19:33:21.328261Z", + "iopub.status.busy": "2024-08-15T19:33:21.327939Z", + "iopub.status.idle": "2024-08-15T19:33:21.330491Z", + "shell.execute_reply": "2024-08-15T19:33:21.330042Z" } }, "outputs": [], @@ -1340,10 +1340,10 @@ "id": "cdf061df", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.310933Z", - "iopub.status.busy": "2024-08-12T18:59:51.310756Z", - "iopub.status.idle": "2024-08-12T18:59:51.314521Z", - "shell.execute_reply": "2024-08-12T18:59:51.314048Z" + "iopub.execute_input": "2024-08-15T19:33:21.332464Z", + "iopub.status.busy": "2024-08-15T19:33:21.332132Z", + "iopub.status.idle": "2024-08-15T19:33:21.335695Z", + "shell.execute_reply": "2024-08-15T19:33:21.335126Z" }, "scrolled": true }, @@ -1395,10 +1395,10 @@ "id": "08949890", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.316522Z", - "iopub.status.busy": "2024-08-12T18:59:51.316329Z", - "iopub.status.idle": "2024-08-12T18:59:51.319058Z", - "shell.execute_reply": "2024-08-12T18:59:51.318594Z" + "iopub.execute_input": "2024-08-15T19:33:21.337813Z", + "iopub.status.busy": "2024-08-15T19:33:21.337495Z", + "iopub.status.idle": "2024-08-15T19:33:21.340157Z", + "shell.execute_reply": "2024-08-15T19:33:21.339711Z" } }, "outputs": [], @@ -1422,10 +1422,10 @@ "id": "6948b073", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.321120Z", - "iopub.status.busy": "2024-08-12T18:59:51.320800Z", - "iopub.status.idle": "2024-08-12T18:59:51.325200Z", - "shell.execute_reply": "2024-08-12T18:59:51.324719Z" + "iopub.execute_input": "2024-08-15T19:33:21.341984Z", + "iopub.status.busy": "2024-08-15T19:33:21.341812Z", + "iopub.status.idle": "2024-08-15T19:33:21.346052Z", + "shell.execute_reply": "2024-08-15T19:33:21.345579Z" } }, "outputs": [ @@ -1480,10 +1480,10 @@ "id": "6f8e6914", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.327285Z", - "iopub.status.busy": "2024-08-12T18:59:51.326972Z", - "iopub.status.idle": "2024-08-12T18:59:51.355218Z", - "shell.execute_reply": "2024-08-12T18:59:51.354758Z" + "iopub.execute_input": "2024-08-15T19:33:21.347925Z", + "iopub.status.busy": "2024-08-15T19:33:21.347755Z", + "iopub.status.idle": "2024-08-15T19:33:21.376149Z", + "shell.execute_reply": "2024-08-15T19:33:21.375710Z" } }, "outputs": [], @@ -1526,10 +1526,10 @@ "id": "b806d2ea", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:51.357340Z", - "iopub.status.busy": "2024-08-12T18:59:51.357164Z", - "iopub.status.idle": "2024-08-12T18:59:51.362121Z", - "shell.execute_reply": "2024-08-12T18:59:51.361539Z" + "iopub.execute_input": "2024-08-15T19:33:21.378033Z", + "iopub.status.busy": "2024-08-15T19:33:21.377852Z", + "iopub.status.idle": "2024-08-15T19:33:21.382432Z", + "shell.execute_reply": "2024-08-15T19:33:21.381970Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/multilabel_classification.ipynb b/master/tutorials/multilabel_classification.ipynb index a251e1b8c..47eee13d5 100644 --- a/master/tutorials/multilabel_classification.ipynb +++ b/master/tutorials/multilabel_classification.ipynb @@ -64,10 +64,10 @@ "id": "7383d024-8273-4039-bccd-aab3020d331f", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:54.476742Z", - "iopub.status.busy": "2024-08-12T18:59:54.476563Z", - "iopub.status.idle": "2024-08-12T18:59:55.941034Z", - "shell.execute_reply": "2024-08-12T18:59:55.940368Z" + "iopub.execute_input": "2024-08-15T19:33:24.408754Z", + "iopub.status.busy": "2024-08-15T19:33:24.408281Z", + "iopub.status.idle": "2024-08-15T19:33:25.784807Z", + "shell.execute_reply": "2024-08-15T19:33:25.784261Z" }, "nbsphinx": "hidden" }, @@ -79,7 +79,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -105,10 +105,10 @@ "id": "bf9101d8-b1a9-4305-b853-45aaf3d67a69", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:55.943675Z", - "iopub.status.busy": "2024-08-12T18:59:55.943355Z", - "iopub.status.idle": "2024-08-12T18:59:55.964343Z", - "shell.execute_reply": "2024-08-12T18:59:55.963737Z" + "iopub.execute_input": "2024-08-15T19:33:25.787291Z", + "iopub.status.busy": "2024-08-15T19:33:25.786884Z", + "iopub.status.idle": "2024-08-15T19:33:25.806389Z", + "shell.execute_reply": "2024-08-15T19:33:25.805835Z" } }, "outputs": [], @@ -268,10 +268,10 @@ "id": "e8ff5c2f-bd52-44aa-b307-b2b634147c68", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:55.967190Z", - "iopub.status.busy": "2024-08-12T18:59:55.966718Z", - "iopub.status.idle": "2024-08-12T18:59:55.980296Z", - "shell.execute_reply": "2024-08-12T18:59:55.979692Z" + "iopub.execute_input": "2024-08-15T19:33:25.808855Z", + "iopub.status.busy": "2024-08-15T19:33:25.808457Z", + "iopub.status.idle": "2024-08-15T19:33:25.821393Z", + "shell.execute_reply": "2024-08-15T19:33:25.820926Z" }, "nbsphinx": "hidden" }, @@ -407,10 +407,10 @@ "id": "dac65d3b-51e8-4682-b829-beab610b56d6", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:55.982590Z", - "iopub.status.busy": "2024-08-12T18:59:55.982109Z", - "iopub.status.idle": "2024-08-12T18:59:58.712481Z", - "shell.execute_reply": "2024-08-12T18:59:58.711874Z" + "iopub.execute_input": "2024-08-15T19:33:25.823364Z", + "iopub.status.busy": "2024-08-15T19:33:25.823058Z", + "iopub.status.idle": "2024-08-15T19:33:28.447593Z", + "shell.execute_reply": "2024-08-15T19:33:28.447075Z" } }, "outputs": [ @@ -454,10 +454,10 @@ "id": "b5fa99a9-2583-4cd0-9d40-015f698cdb23", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T18:59:58.714680Z", - "iopub.status.busy": "2024-08-12T18:59:58.714484Z", - "iopub.status.idle": "2024-08-12T19:00:00.087689Z", - "shell.execute_reply": "2024-08-12T19:00:00.087120Z" + "iopub.execute_input": "2024-08-15T19:33:28.449922Z", + "iopub.status.busy": "2024-08-15T19:33:28.449570Z", + "iopub.status.idle": "2024-08-15T19:33:29.787510Z", + "shell.execute_reply": "2024-08-15T19:33:29.786948Z" } }, "outputs": [], @@ -499,10 +499,10 @@ "id": "ac1a60df", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:00.090114Z", - "iopub.status.busy": "2024-08-12T19:00:00.089917Z", - "iopub.status.idle": "2024-08-12T19:00:00.094093Z", - "shell.execute_reply": "2024-08-12T19:00:00.093606Z" + "iopub.execute_input": "2024-08-15T19:33:29.789829Z", + "iopub.status.busy": "2024-08-15T19:33:29.789481Z", + "iopub.status.idle": "2024-08-15T19:33:29.793115Z", + "shell.execute_reply": "2024-08-15T19:33:29.792575Z" } }, "outputs": [ @@ -544,10 +544,10 @@ "id": "d09115b6-ad44-474f-9c8a-85a459586439", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:00.096133Z", - "iopub.status.busy": "2024-08-12T19:00:00.095947Z", - "iopub.status.idle": "2024-08-12T19:00:02.393180Z", - "shell.execute_reply": "2024-08-12T19:00:02.392409Z" + "iopub.execute_input": "2024-08-15T19:33:29.795208Z", + "iopub.status.busy": "2024-08-15T19:33:29.794902Z", + "iopub.status.idle": "2024-08-15T19:33:31.847436Z", + "shell.execute_reply": "2024-08-15T19:33:31.846807Z" } }, "outputs": [ @@ -594,10 +594,10 @@ "id": "c18dd83b", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:02.395957Z", - "iopub.status.busy": "2024-08-12T19:00:02.395557Z", - "iopub.status.idle": "2024-08-12T19:00:02.404909Z", - "shell.execute_reply": "2024-08-12T19:00:02.404317Z" + "iopub.execute_input": "2024-08-15T19:33:31.849932Z", + "iopub.status.busy": "2024-08-15T19:33:31.849463Z", + "iopub.status.idle": "2024-08-15T19:33:31.857663Z", + "shell.execute_reply": "2024-08-15T19:33:31.857099Z" } }, "outputs": [ @@ -633,10 +633,10 @@ "id": "fffa88f6-84d7-45fe-8214-0e22079a06d1", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:02.407237Z", - "iopub.status.busy": "2024-08-12T19:00:02.406886Z", - "iopub.status.idle": "2024-08-12T19:00:05.052633Z", - "shell.execute_reply": "2024-08-12T19:00:05.051949Z" + "iopub.execute_input": "2024-08-15T19:33:31.859866Z", + "iopub.status.busy": "2024-08-15T19:33:31.859532Z", + "iopub.status.idle": "2024-08-15T19:33:34.428636Z", + "shell.execute_reply": "2024-08-15T19:33:34.428080Z" } }, "outputs": [ @@ -671,10 +671,10 @@ "id": "c1198575", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:05.055108Z", - "iopub.status.busy": "2024-08-12T19:00:05.054701Z", - "iopub.status.idle": "2024-08-12T19:00:05.058341Z", - "shell.execute_reply": "2024-08-12T19:00:05.057777Z" + "iopub.execute_input": "2024-08-15T19:33:34.431112Z", + "iopub.status.busy": "2024-08-15T19:33:34.430687Z", + "iopub.status.idle": "2024-08-15T19:33:34.434117Z", + "shell.execute_reply": "2024-08-15T19:33:34.433576Z" } }, "outputs": [ @@ -721,10 +721,10 @@ "id": "49161b19-7625-4fb7-add9-607d91a7eca1", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:05.060592Z", - "iopub.status.busy": "2024-08-12T19:00:05.060231Z", - "iopub.status.idle": "2024-08-12T19:00:05.064081Z", - "shell.execute_reply": "2024-08-12T19:00:05.063515Z" + "iopub.execute_input": "2024-08-15T19:33:34.436313Z", + "iopub.status.busy": "2024-08-15T19:33:34.435988Z", + "iopub.status.idle": "2024-08-15T19:33:34.439420Z", + "shell.execute_reply": "2024-08-15T19:33:34.438961Z" } }, "outputs": [], @@ -769,10 +769,10 @@ "id": "d1a2c008", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:05.066213Z", - "iopub.status.busy": "2024-08-12T19:00:05.066030Z", - "iopub.status.idle": "2024-08-12T19:00:05.069385Z", - "shell.execute_reply": "2024-08-12T19:00:05.068796Z" + "iopub.execute_input": "2024-08-15T19:33:34.441508Z", + "iopub.status.busy": "2024-08-15T19:33:34.441183Z", + "iopub.status.idle": "2024-08-15T19:33:34.444382Z", + "shell.execute_reply": "2024-08-15T19:33:34.443828Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/object_detection.ipynb b/master/tutorials/object_detection.ipynb index 825856313..0ddc47a57 100644 --- a/master/tutorials/object_detection.ipynb +++ b/master/tutorials/object_detection.ipynb @@ -70,10 +70,10 @@ "id": "0ba0dc70", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:07.744973Z", - "iopub.status.busy": "2024-08-12T19:00:07.744802Z", - "iopub.status.idle": "2024-08-12T19:00:09.232129Z", - "shell.execute_reply": "2024-08-12T19:00:09.231463Z" + "iopub.execute_input": "2024-08-15T19:33:37.019527Z", + "iopub.status.busy": "2024-08-15T19:33:37.019170Z", + "iopub.status.idle": "2024-08-15T19:33:38.388227Z", + "shell.execute_reply": "2024-08-15T19:33:38.387596Z" }, "nbsphinx": "hidden" }, @@ -83,7 +83,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -109,10 +109,10 @@ "id": "c90449c8", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:09.234897Z", - "iopub.status.busy": "2024-08-12T19:00:09.234541Z", - "iopub.status.idle": "2024-08-12T19:00:11.915101Z", - "shell.execute_reply": "2024-08-12T19:00:11.914359Z" + "iopub.execute_input": "2024-08-15T19:33:38.390795Z", + "iopub.status.busy": "2024-08-15T19:33:38.390519Z", + "iopub.status.idle": "2024-08-15T19:33:39.912137Z", + "shell.execute_reply": "2024-08-15T19:33:39.911322Z" } }, "outputs": [], @@ -130,10 +130,10 @@ "id": "df8be4c6", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:11.917833Z", - "iopub.status.busy": "2024-08-12T19:00:11.917612Z", - "iopub.status.idle": "2024-08-12T19:00:11.921571Z", - "shell.execute_reply": "2024-08-12T19:00:11.921101Z" + "iopub.execute_input": "2024-08-15T19:33:39.914956Z", + "iopub.status.busy": "2024-08-15T19:33:39.914717Z", + "iopub.status.idle": "2024-08-15T19:33:39.918337Z", + "shell.execute_reply": "2024-08-15T19:33:39.917863Z" } }, "outputs": [], @@ -169,10 +169,10 @@ "id": "2e9ffd6f", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:11.923756Z", - "iopub.status.busy": "2024-08-12T19:00:11.923398Z", - "iopub.status.idle": "2024-08-12T19:00:11.931022Z", - "shell.execute_reply": "2024-08-12T19:00:11.930496Z" + "iopub.execute_input": "2024-08-15T19:33:39.920645Z", + "iopub.status.busy": "2024-08-15T19:33:39.920144Z", + "iopub.status.idle": "2024-08-15T19:33:39.927984Z", + "shell.execute_reply": "2024-08-15T19:33:39.927424Z" } }, "outputs": [], @@ -198,10 +198,10 @@ "id": "56705562", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:11.933415Z", - "iopub.status.busy": "2024-08-12T19:00:11.933040Z", - "iopub.status.idle": "2024-08-12T19:00:12.256254Z", - "shell.execute_reply": "2024-08-12T19:00:12.255623Z" + "iopub.execute_input": "2024-08-15T19:33:39.930288Z", + "iopub.status.busy": "2024-08-15T19:33:39.929871Z", + "iopub.status.idle": "2024-08-15T19:33:40.245021Z", + "shell.execute_reply": "2024-08-15T19:33:40.244466Z" }, "scrolled": true }, @@ -242,10 +242,10 @@ "id": "b08144d7", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:12.259525Z", - "iopub.status.busy": "2024-08-12T19:00:12.259155Z", - "iopub.status.idle": "2024-08-12T19:00:12.265184Z", - "shell.execute_reply": "2024-08-12T19:00:12.264699Z" + "iopub.execute_input": "2024-08-15T19:33:40.247559Z", + "iopub.status.busy": "2024-08-15T19:33:40.247387Z", + "iopub.status.idle": "2024-08-15T19:33:40.252844Z", + "shell.execute_reply": "2024-08-15T19:33:40.252371Z" } }, "outputs": [ @@ -497,10 +497,10 @@ "id": "3d70bec6", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:12.267306Z", - "iopub.status.busy": "2024-08-12T19:00:12.266962Z", - "iopub.status.idle": "2024-08-12T19:00:12.270759Z", - "shell.execute_reply": "2024-08-12T19:00:12.270274Z" + "iopub.execute_input": "2024-08-15T19:33:40.254902Z", + "iopub.status.busy": "2024-08-15T19:33:40.254449Z", + "iopub.status.idle": "2024-08-15T19:33:40.258381Z", + "shell.execute_reply": "2024-08-15T19:33:40.257857Z" } }, "outputs": [ @@ -557,10 +557,10 @@ "id": "4caa635d", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:12.272845Z", - "iopub.status.busy": "2024-08-12T19:00:12.272501Z", - "iopub.status.idle": "2024-08-12T19:00:13.251328Z", - "shell.execute_reply": "2024-08-12T19:00:13.250639Z" + "iopub.execute_input": "2024-08-15T19:33:40.260446Z", + "iopub.status.busy": "2024-08-15T19:33:40.260109Z", + "iopub.status.idle": "2024-08-15T19:33:41.265411Z", + "shell.execute_reply": "2024-08-15T19:33:41.264860Z" } }, "outputs": [ @@ -616,10 +616,10 @@ "id": "a9b4c590", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:13.253843Z", - "iopub.status.busy": "2024-08-12T19:00:13.253432Z", - "iopub.status.idle": "2024-08-12T19:00:13.457386Z", - "shell.execute_reply": "2024-08-12T19:00:13.456904Z" + "iopub.execute_input": "2024-08-15T19:33:41.267651Z", + "iopub.status.busy": "2024-08-15T19:33:41.267464Z", + "iopub.status.idle": "2024-08-15T19:33:41.466081Z", + "shell.execute_reply": "2024-08-15T19:33:41.465642Z" } }, "outputs": [ @@ -660,10 +660,10 @@ "id": "ffd9ebcc", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:13.459660Z", - "iopub.status.busy": "2024-08-12T19:00:13.459285Z", - "iopub.status.idle": "2024-08-12T19:00:13.463485Z", - "shell.execute_reply": "2024-08-12T19:00:13.462963Z" + "iopub.execute_input": "2024-08-15T19:33:41.468250Z", + "iopub.status.busy": "2024-08-15T19:33:41.467912Z", + "iopub.status.idle": "2024-08-15T19:33:41.471774Z", + "shell.execute_reply": "2024-08-15T19:33:41.471263Z" } }, "outputs": [ @@ -700,10 +700,10 @@ "id": "4dd46d67", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:13.465606Z", - "iopub.status.busy": "2024-08-12T19:00:13.465247Z", - "iopub.status.idle": "2024-08-12T19:00:13.843786Z", - "shell.execute_reply": "2024-08-12T19:00:13.843149Z" + "iopub.execute_input": "2024-08-15T19:33:41.473778Z", + "iopub.status.busy": "2024-08-15T19:33:41.473449Z", + "iopub.status.idle": "2024-08-15T19:33:41.842101Z", + "shell.execute_reply": "2024-08-15T19:33:41.841613Z" } }, "outputs": [ @@ -762,10 +762,10 @@ "id": "ceec2394", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:13.846938Z", - "iopub.status.busy": "2024-08-12T19:00:13.846715Z", - "iopub.status.idle": "2024-08-12T19:00:14.186146Z", - "shell.execute_reply": "2024-08-12T19:00:14.185542Z" + "iopub.execute_input": "2024-08-15T19:33:41.845280Z", + "iopub.status.busy": "2024-08-15T19:33:41.844906Z", + "iopub.status.idle": "2024-08-15T19:33:42.175876Z", + "shell.execute_reply": "2024-08-15T19:33:42.175343Z" } }, "outputs": [ @@ -812,10 +812,10 @@ "id": "94f82b0d", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:14.189289Z", - "iopub.status.busy": "2024-08-12T19:00:14.188801Z", - "iopub.status.idle": "2024-08-12T19:00:14.531251Z", - "shell.execute_reply": "2024-08-12T19:00:14.530600Z" + "iopub.execute_input": "2024-08-15T19:33:42.178463Z", + "iopub.status.busy": "2024-08-15T19:33:42.178100Z", + "iopub.status.idle": "2024-08-15T19:33:42.540455Z", + "shell.execute_reply": "2024-08-15T19:33:42.539894Z" } }, "outputs": [ @@ -862,10 +862,10 @@ "id": "1ea18c5d", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:14.534669Z", - "iopub.status.busy": "2024-08-12T19:00:14.534462Z", - "iopub.status.idle": "2024-08-12T19:00:14.981300Z", - "shell.execute_reply": "2024-08-12T19:00:14.980718Z" + "iopub.execute_input": "2024-08-15T19:33:42.543382Z", + "iopub.status.busy": "2024-08-15T19:33:42.543022Z", + "iopub.status.idle": "2024-08-15T19:33:42.954896Z", + "shell.execute_reply": "2024-08-15T19:33:42.954295Z" } }, "outputs": [ @@ -925,10 +925,10 @@ "id": "7e770d23", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:14.986021Z", - "iopub.status.busy": "2024-08-12T19:00:14.985784Z", - "iopub.status.idle": "2024-08-12T19:00:15.419680Z", - "shell.execute_reply": "2024-08-12T19:00:15.419087Z" + "iopub.execute_input": "2024-08-15T19:33:42.959199Z", + "iopub.status.busy": "2024-08-15T19:33:42.958898Z", + "iopub.status.idle": "2024-08-15T19:33:43.382799Z", + "shell.execute_reply": "2024-08-15T19:33:43.382192Z" } }, "outputs": [ @@ -971,10 +971,10 @@ "id": "57e84a27", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:15.423219Z", - "iopub.status.busy": "2024-08-12T19:00:15.422852Z", - "iopub.status.idle": "2024-08-12T19:00:15.641955Z", - "shell.execute_reply": "2024-08-12T19:00:15.641306Z" + "iopub.execute_input": "2024-08-15T19:33:43.385956Z", + "iopub.status.busy": "2024-08-15T19:33:43.385755Z", + "iopub.status.idle": "2024-08-15T19:33:43.602082Z", + "shell.execute_reply": "2024-08-15T19:33:43.601513Z" } }, "outputs": [ @@ -1017,10 +1017,10 @@ "id": "0302818a", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:15.644256Z", - "iopub.status.busy": "2024-08-12T19:00:15.643880Z", - "iopub.status.idle": "2024-08-12T19:00:15.829580Z", - "shell.execute_reply": "2024-08-12T19:00:15.828972Z" + "iopub.execute_input": "2024-08-15T19:33:43.604528Z", + "iopub.status.busy": "2024-08-15T19:33:43.604168Z", + "iopub.status.idle": "2024-08-15T19:33:43.806270Z", + "shell.execute_reply": "2024-08-15T19:33:43.805784Z" } }, "outputs": [ @@ -1067,10 +1067,10 @@ "id": "5cacec81-2adf-46a8-82c5-7ec0185d4356", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:15.831912Z", - "iopub.status.busy": "2024-08-12T19:00:15.831726Z", - "iopub.status.idle": "2024-08-12T19:00:15.834898Z", - "shell.execute_reply": "2024-08-12T19:00:15.834335Z" + "iopub.execute_input": "2024-08-15T19:33:43.808569Z", + "iopub.status.busy": "2024-08-15T19:33:43.808203Z", + "iopub.status.idle": "2024-08-15T19:33:43.811161Z", + "shell.execute_reply": "2024-08-15T19:33:43.810678Z" } }, "outputs": [], @@ -1090,10 +1090,10 @@ "id": "3335b8a3-d0b4-415a-a97d-c203088a124e", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:15.837304Z", - "iopub.status.busy": "2024-08-12T19:00:15.837106Z", - "iopub.status.idle": "2024-08-12T19:00:16.840169Z", - "shell.execute_reply": "2024-08-12T19:00:16.839611Z" + "iopub.execute_input": "2024-08-15T19:33:43.813139Z", + "iopub.status.busy": "2024-08-15T19:33:43.812803Z", + "iopub.status.idle": "2024-08-15T19:33:44.706006Z", + "shell.execute_reply": "2024-08-15T19:33:44.705477Z" } }, "outputs": [ @@ -1172,10 +1172,10 @@ "id": "9d4b7677-6ebd-447d-b0a1-76e094686628", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:16.842986Z", - "iopub.status.busy": "2024-08-12T19:00:16.842795Z", - "iopub.status.idle": "2024-08-12T19:00:17.013055Z", - "shell.execute_reply": "2024-08-12T19:00:17.012447Z" + "iopub.execute_input": "2024-08-15T19:33:44.708884Z", + "iopub.status.busy": "2024-08-15T19:33:44.708480Z", + "iopub.status.idle": "2024-08-15T19:33:44.825603Z", + "shell.execute_reply": "2024-08-15T19:33:44.825038Z" } }, "outputs": [ @@ -1214,10 +1214,10 @@ "id": "59d7ee39-3785-434b-8680-9133014851cd", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:17.015418Z", - "iopub.status.busy": "2024-08-12T19:00:17.014952Z", - "iopub.status.idle": "2024-08-12T19:00:17.154380Z", - "shell.execute_reply": "2024-08-12T19:00:17.153704Z" + "iopub.execute_input": "2024-08-15T19:33:44.827802Z", + "iopub.status.busy": "2024-08-15T19:33:44.827471Z", + "iopub.status.idle": "2024-08-15T19:33:44.952068Z", + "shell.execute_reply": "2024-08-15T19:33:44.951643Z" } }, "outputs": [], @@ -1266,10 +1266,10 @@ "id": "47b6a8ff-7a58-4a1f-baee-e6cfe7a85a6d", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:17.157210Z", - "iopub.status.busy": "2024-08-12T19:00:17.156832Z", - "iopub.status.idle": "2024-08-12T19:00:17.940088Z", - "shell.execute_reply": "2024-08-12T19:00:17.939515Z" + "iopub.execute_input": "2024-08-15T19:33:44.954099Z", + "iopub.status.busy": "2024-08-15T19:33:44.953765Z", + "iopub.status.idle": "2024-08-15T19:33:45.616770Z", + "shell.execute_reply": "2024-08-15T19:33:45.616095Z" } }, "outputs": [ @@ -1351,10 +1351,10 @@ "id": "8ce74938", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:17.942465Z", - "iopub.status.busy": "2024-08-12T19:00:17.942094Z", - "iopub.status.idle": "2024-08-12T19:00:17.945988Z", - "shell.execute_reply": "2024-08-12T19:00:17.945408Z" + "iopub.execute_input": "2024-08-15T19:33:45.619455Z", + "iopub.status.busy": "2024-08-15T19:33:45.619011Z", + "iopub.status.idle": "2024-08-15T19:33:45.623830Z", + "shell.execute_reply": "2024-08-15T19:33:45.623366Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/outliers.html b/master/tutorials/outliers.html index 9b9466013..96d9f7fe4 100644 --- a/master/tutorials/outliers.html +++ b/master/tutorials/outliers.html @@ -780,7 +780,7 @@

    2. Pre-process the Cifar10 dataset 
    -100%|██████████| 170498071/170498071 [00:04<00:00, 40165594.79it/s]
+100%|██████████| 170498071/170498071 [00:01<00:00, 104640519.71it/s]
    @@ -910,7 +910,7 @@

    3. Use cleanlab and feature embeddings to find outliers in the data

    -
    +
    @@ -1130,7 +1130,7 @@

    Spending too much time on data quality?Cleanlab Studio – an automated platform to find and fix issues in your dataset, 100x faster and more accurately. Cleanlab Studio automatically runs optimized data quality algorithms from this package on top of cutting-edge AutoML & Foundation models fit to your data, and helps you fix detected issues via a smart data correction interface. Try it for free!

    The modern AI pipeline automated with Cleanlab Studio

    diff --git a/master/tutorials/outliers.ipynb b/master/tutorials/outliers.ipynb index 29b2c9f91..f4aab066c 100644 --- a/master/tutorials/outliers.ipynb +++ b/master/tutorials/outliers.ipynb @@ -109,10 +109,10 @@ "id": "2bbebfc8", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:20.285190Z", - "iopub.status.busy": "2024-08-12T19:00:20.285019Z", - "iopub.status.idle": "2024-08-12T19:00:23.633953Z", - "shell.execute_reply": "2024-08-12T19:00:23.633344Z" + "iopub.execute_input": "2024-08-15T19:33:47.753920Z", + "iopub.status.busy": "2024-08-15T19:33:47.753743Z", + "iopub.status.idle": "2024-08-15T19:33:50.873837Z", + "shell.execute_reply": "2024-08-15T19:33:50.873200Z" }, "nbsphinx": "hidden" }, @@ -125,7 +125,7 @@ "dependencies = [\"matplotlib\", \"torch\", \"torchvision\", \"timm\", \"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -159,10 +159,10 @@ "id": "4396f544", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:23.636656Z", - "iopub.status.busy": "2024-08-12T19:00:23.636296Z", - "iopub.status.idle": "2024-08-12T19:00:23.656607Z", - "shell.execute_reply": "2024-08-12T19:00:23.656031Z" + "iopub.execute_input": "2024-08-15T19:33:50.876385Z", + "iopub.status.busy": "2024-08-15T19:33:50.876125Z", + "iopub.status.idle": "2024-08-15T19:33:50.894998Z", + "shell.execute_reply": "2024-08-15T19:33:50.894410Z" } }, "outputs": [], @@ -188,10 +188,10 @@ "id": "3792f82e", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:23.659450Z", - "iopub.status.busy": "2024-08-12T19:00:23.658866Z", - "iopub.status.idle": "2024-08-12T19:00:23.663050Z", - "shell.execute_reply": "2024-08-12T19:00:23.662569Z" + "iopub.execute_input": "2024-08-15T19:33:50.897311Z", + "iopub.status.busy": "2024-08-15T19:33:50.896794Z", + "iopub.status.idle": "2024-08-15T19:33:50.900895Z", + "shell.execute_reply": "2024-08-15T19:33:50.900340Z" }, "nbsphinx": "hidden" }, @@ -225,10 +225,10 @@ "id": "fd853a54", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:23.665359Z", - "iopub.status.busy": "2024-08-12T19:00:23.665006Z", - "iopub.status.idle": "2024-08-12T19:00:31.351770Z", - "shell.execute_reply": "2024-08-12T19:00:31.351225Z" + "iopub.execute_input": "2024-08-15T19:33:50.903083Z", + "iopub.status.busy": "2024-08-15T19:33:50.902737Z", + "iopub.status.idle": "2024-08-15T19:33:55.313541Z", + "shell.execute_reply": "2024-08-15T19:33:55.313007Z" } }, "outputs": [ @@ -252,7 +252,7 @@ "output_type": "stream", "text": [ "\r", - " 0%| | 32768/170498071 [00:00<11:24, 249157.84it/s]" + " 1%|▏ | 2162688/170498071 [00:00<00:07, 21623910.41it/s]" ] }, { @@ -260,7 +260,7 @@ "output_type": "stream", "text": [ "\r", - " 0%| | 196608/170498071 [00:00<03:25, 827471.69it/s]" + " 8%|▊ | 13107200/170498071 [00:00<00:02, 73070189.60it/s]" ] }, { @@ -268,7 +268,7 @@ "output_type": "stream", "text": [ "\r", - " 0%| | 819200/170498071 [00:00<01:05, 2583423.64it/s]" + " 14%|█▍ | 24215552/170498071 [00:00<00:01, 90380625.90it/s]" ] }, { @@ -276,7 +276,7 @@ "output_type": "stream", "text": [ "\r", - 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"iopub.execute_input": "2024-08-12T19:00:31.354406Z", - "iopub.status.busy": "2024-08-12T19:00:31.353939Z", - "iopub.status.idle": "2024-08-12T19:00:31.358764Z", - "shell.execute_reply": "2024-08-12T19:00:31.358312Z" + "iopub.execute_input": "2024-08-15T19:33:55.315768Z", + "iopub.status.busy": "2024-08-15T19:33:55.315488Z", + "iopub.status.idle": "2024-08-15T19:33:55.320319Z", + "shell.execute_reply": "2024-08-15T19:33:55.319873Z" }, "nbsphinx": "hidden" }, @@ -736,10 +552,10 @@ "id": "a00aa3ed", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:31.360792Z", - "iopub.status.busy": "2024-08-12T19:00:31.360605Z", - "iopub.status.idle": "2024-08-12T19:00:31.923812Z", - "shell.execute_reply": "2024-08-12T19:00:31.923180Z" + "iopub.execute_input": "2024-08-15T19:33:55.322345Z", + "iopub.status.busy": "2024-08-15T19:33:55.322005Z", + "iopub.status.idle": "2024-08-15T19:33:55.863016Z", + "shell.execute_reply": "2024-08-15T19:33:55.862471Z" } }, "outputs": [ @@ -772,10 +588,10 @@ "id": "41e5cb6b", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:31.926228Z", - "iopub.status.busy": "2024-08-12T19:00:31.925847Z", - "iopub.status.idle": "2024-08-12T19:00:32.452460Z", - "shell.execute_reply": "2024-08-12T19:00:32.451834Z" + "iopub.execute_input": "2024-08-15T19:33:55.865045Z", + "iopub.status.busy": "2024-08-15T19:33:55.864865Z", + "iopub.status.idle": "2024-08-15T19:33:56.372326Z", + "shell.execute_reply": "2024-08-15T19:33:56.371835Z" } }, "outputs": [ @@ -813,10 +629,10 @@ "id": "1cf25354", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:32.454955Z", - "iopub.status.busy": "2024-08-12T19:00:32.454540Z", - "iopub.status.idle": "2024-08-12T19:00:32.457996Z", - "shell.execute_reply": "2024-08-12T19:00:32.457535Z" + "iopub.execute_input": "2024-08-15T19:33:56.374382Z", + "iopub.status.busy": "2024-08-15T19:33:56.374193Z", + "iopub.status.idle": "2024-08-15T19:33:56.377844Z", + "shell.execute_reply": "2024-08-15T19:33:56.377394Z" } }, "outputs": [], @@ -839,17 +655,17 @@ "id": "85a58d41", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:32.459913Z", - "iopub.status.busy": "2024-08-12T19:00:32.459734Z", - "iopub.status.idle": "2024-08-12T19:00:45.325277Z", - "shell.execute_reply": "2024-08-12T19:00:45.324697Z" + "iopub.execute_input": "2024-08-15T19:33:56.379645Z", + "iopub.status.busy": "2024-08-15T19:33:56.379475Z", + "iopub.status.idle": "2024-08-15T19:34:08.626829Z", + "shell.execute_reply": "2024-08-15T19:34:08.626231Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7e4fc5c79f684873aca29643ab5213d6", + "model_id": "f7926ed22a844edd98f972b00aa940cf", "version_major": 2, "version_minor": 0 }, @@ -908,10 +724,10 @@ "id": "feb0f519", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:45.327911Z", - "iopub.status.busy": "2024-08-12T19:00:45.327546Z", - "iopub.status.idle": "2024-08-12T19:00:47.473285Z", - "shell.execute_reply": "2024-08-12T19:00:47.472582Z" + "iopub.execute_input": "2024-08-15T19:34:08.629376Z", + "iopub.status.busy": "2024-08-15T19:34:08.629024Z", + "iopub.status.idle": "2024-08-15T19:34:10.730658Z", + "shell.execute_reply": "2024-08-15T19:34:10.730020Z" } }, "outputs": [ @@ -955,10 +771,10 @@ "id": "089d5860", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:47.476197Z", - "iopub.status.busy": "2024-08-12T19:00:47.475653Z", - "iopub.status.idle": "2024-08-12T19:00:47.741842Z", - "shell.execute_reply": "2024-08-12T19:00:47.741157Z" + "iopub.execute_input": "2024-08-15T19:34:10.733233Z", + "iopub.status.busy": "2024-08-15T19:34:10.732753Z", + "iopub.status.idle": "2024-08-15T19:34:10.984048Z", + "shell.execute_reply": "2024-08-15T19:34:10.983415Z" } }, "outputs": [ @@ -994,10 +810,10 @@ "id": "78b1951c", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:47.744874Z", - "iopub.status.busy": "2024-08-12T19:00:47.744331Z", - "iopub.status.idle": "2024-08-12T19:00:48.420941Z", - "shell.execute_reply": "2024-08-12T19:00:48.420354Z" + "iopub.execute_input": "2024-08-15T19:34:10.986867Z", + "iopub.status.busy": "2024-08-15T19:34:10.986378Z", + "iopub.status.idle": "2024-08-15T19:34:11.674841Z", + "shell.execute_reply": "2024-08-15T19:34:11.674279Z" } }, "outputs": [ @@ -1047,10 +863,10 @@ "id": "e9dff81b", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:48.423834Z", - "iopub.status.busy": "2024-08-12T19:00:48.423300Z", - "iopub.status.idle": "2024-08-12T19:00:48.777069Z", - "shell.execute_reply": "2024-08-12T19:00:48.776492Z" + "iopub.execute_input": "2024-08-15T19:34:11.677813Z", + "iopub.status.busy": "2024-08-15T19:34:11.677368Z", + "iopub.status.idle": "2024-08-15T19:34:12.014922Z", + "shell.execute_reply": "2024-08-15T19:34:12.014402Z" } }, "outputs": [ @@ -1098,10 +914,10 @@ "id": "616769f8", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:48.779436Z", - "iopub.status.busy": "2024-08-12T19:00:48.779092Z", - "iopub.status.idle": "2024-08-12T19:00:49.030804Z", - "shell.execute_reply": "2024-08-12T19:00:49.030162Z" + "iopub.execute_input": "2024-08-15T19:34:12.017074Z", + "iopub.status.busy": "2024-08-15T19:34:12.016728Z", + "iopub.status.idle": "2024-08-15T19:34:12.256278Z", + "shell.execute_reply": "2024-08-15T19:34:12.255674Z" } }, "outputs": [ @@ -1157,10 +973,10 @@ "id": "40fed4ef", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:49.033695Z", - "iopub.status.busy": "2024-08-12T19:00:49.033452Z", - "iopub.status.idle": "2024-08-12T19:00:49.129989Z", - "shell.execute_reply": "2024-08-12T19:00:49.129464Z" + "iopub.execute_input": "2024-08-15T19:34:12.259413Z", + "iopub.status.busy": "2024-08-15T19:34:12.258693Z", + "iopub.status.idle": "2024-08-15T19:34:12.349564Z", + "shell.execute_reply": "2024-08-15T19:34:12.349074Z" } }, "outputs": [], @@ -1181,10 +997,10 @@ "id": "89f9db72", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:00:49.132284Z", - "iopub.status.busy": "2024-08-12T19:00:49.132107Z", - "iopub.status.idle": "2024-08-12T19:00:59.836874Z", - "shell.execute_reply": "2024-08-12T19:00:59.836169Z" + "iopub.execute_input": "2024-08-15T19:34:12.352057Z", + "iopub.status.busy": "2024-08-15T19:34:12.351708Z", + "iopub.status.idle": "2024-08-15T19:34:22.676851Z", + "shell.execute_reply": "2024-08-15T19:34:22.676176Z" } }, "outputs": [ @@ -1221,10 +1037,10 @@ "id": "874c885a", "metadata": { "execution": { - 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"iopub.execute_input": "2024-08-12T19:01:02.435897Z", - "iopub.status.busy": "2024-08-12T19:01:02.435430Z", - "iopub.status.idle": "2024-08-12T19:01:02.438731Z", - "shell.execute_reply": "2024-08-12T19:01:02.438202Z" + "iopub.execute_input": "2024-08-15T19:34:25.124151Z", + "iopub.status.busy": "2024-08-15T19:34:25.123797Z", + "iopub.status.idle": "2024-08-15T19:34:25.126846Z", + "shell.execute_reply": "2024-08-15T19:34:25.126423Z" } }, "outputs": [], @@ -1313,10 +1129,10 @@ "id": "17f96fa6", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:02.440833Z", - "iopub.status.busy": "2024-08-12T19:01:02.440515Z", - "iopub.status.idle": "2024-08-12T19:01:02.448965Z", - "shell.execute_reply": "2024-08-12T19:01:02.448383Z" + "iopub.execute_input": "2024-08-15T19:34:25.128796Z", + "iopub.status.busy": "2024-08-15T19:34:25.128505Z", + "iopub.status.idle": "2024-08-15T19:34:25.137369Z", + "shell.execute_reply": "2024-08-15T19:34:25.136809Z" }, "nbsphinx": "hidden" }, @@ -1361,7 +1177,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - 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"_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_fc42d1facc844e459afc09ef7c687042", - "IPY_MODEL_f86698037fa647aca0a9fa209c430b2b", - "IPY_MODEL_90831226eb3e4b068e5309c838071a8c" - ], - "layout": "IPY_MODEL_691cb5820f224f97a76ae4bde2e746e6", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_1a1b0d232b024e53a1e81344e527587a", + "placeholder": "​", + "style": "IPY_MODEL_3a0e9da941fd43f2b03275bc58fc0705", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": "model.safetensors: 100%" } }, - "90831226eb3e4b068e5309c838071a8c": { + "e9b1a1c680a24a3e9b0aee604b559e7f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1559,15 +1452,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_281d904d63634ba2bc515e56e280b18a", + "layout": "IPY_MODEL_406132a528264560a11c9e77f4f2e58c", "placeholder": "​", - "style": "IPY_MODEL_9f62f6674a964c1aa565f872301096e5", + "style": "IPY_MODEL_400120aefdbb480a822fed3d676395fc", "tabbable": null, "tooltip": null, - "value": " 102M/102M [00:00<00:00, 205MB/s]" + "value": " 102M/102M [00:00<00:00, 303MB/s]" } }, - "924131cdce89473fb5ed8528e97a50f1": { + "ebce44de0fe949b1acf4ec52d4316286": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1620,105 +1513,28 @@ "width": null } }, - "9f62f6674a964c1aa565f872301096e5": { + "f7926ed22a844edd98f972b00aa940cf": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - 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"model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_370d465ea34c4da9906a0a85d82d056b", - "placeholder": "​", - "style": "IPY_MODEL_b47804059351482a8c58b8dda5743345", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_9b899db2f69d44398458f3843f327db9", + "IPY_MODEL_3a035619b39f4f869c0ca82a4fc4ed45", + "IPY_MODEL_e9b1a1c680a24a3e9b0aee604b559e7f" + ], + "layout": "IPY_MODEL_989e4c77eb4b4c188be3b9f9626ed64f", "tabbable": null, - "tooltip": null, - "value": "model.safetensors: 100%" + "tooltip": null } } }, diff --git a/master/tutorials/regression.ipynb b/master/tutorials/regression.ipynb index 76fbdefa7..4f47e7f81 100644 --- a/master/tutorials/regression.ipynb +++ b/master/tutorials/regression.ipynb @@ -102,10 +102,10 @@ "id": "2e1af7d8", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:06.712529Z", - "iopub.status.busy": "2024-08-12T19:01:06.712319Z", - "iopub.status.idle": "2024-08-12T19:01:08.153165Z", - "shell.execute_reply": "2024-08-12T19:01:08.152492Z" + "iopub.execute_input": "2024-08-15T19:34:29.375142Z", + "iopub.status.busy": "2024-08-15T19:34:29.374663Z", + "iopub.status.idle": "2024-08-15T19:34:30.757000Z", + "shell.execute_reply": "2024-08-15T19:34:30.756364Z" }, "nbsphinx": "hidden" }, @@ -116,7 +116,7 @@ "dependencies = [\"cleanlab\", \"matplotlib>=3.6.0\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = \" \".join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -142,10 +142,10 @@ "id": "4fb10b8f", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.155797Z", - "iopub.status.busy": "2024-08-12T19:01:08.155495Z", - "iopub.status.idle": "2024-08-12T19:01:08.174435Z", - "shell.execute_reply": "2024-08-12T19:01:08.173861Z" + "iopub.execute_input": "2024-08-15T19:34:30.759704Z", + "iopub.status.busy": "2024-08-15T19:34:30.759397Z", + "iopub.status.idle": "2024-08-15T19:34:30.777754Z", + "shell.execute_reply": "2024-08-15T19:34:30.777305Z" } }, "outputs": [], @@ -164,10 +164,10 @@ "id": "284dc264", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.177045Z", - "iopub.status.busy": "2024-08-12T19:01:08.176495Z", - "iopub.status.idle": "2024-08-12T19:01:08.179648Z", - "shell.execute_reply": "2024-08-12T19:01:08.179143Z" + "iopub.execute_input": "2024-08-15T19:34:30.779717Z", + "iopub.status.busy": "2024-08-15T19:34:30.779446Z", + "iopub.status.idle": "2024-08-15T19:34:30.782513Z", + "shell.execute_reply": "2024-08-15T19:34:30.782070Z" }, "nbsphinx": "hidden" }, @@ -198,10 +198,10 @@ "id": "0f7450db", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.181771Z", - "iopub.status.busy": "2024-08-12T19:01:08.181384Z", - "iopub.status.idle": "2024-08-12T19:01:08.453781Z", - "shell.execute_reply": "2024-08-12T19:01:08.453196Z" + "iopub.execute_input": "2024-08-15T19:34:30.784432Z", + "iopub.status.busy": "2024-08-15T19:34:30.784259Z", + "iopub.status.idle": "2024-08-15T19:34:30.889118Z", + "shell.execute_reply": "2024-08-15T19:34:30.888654Z" } }, "outputs": [ @@ -374,10 +374,10 @@ "id": "55513fed", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.456263Z", - "iopub.status.busy": "2024-08-12T19:01:08.455844Z", - "iopub.status.idle": "2024-08-12T19:01:08.460424Z", - "shell.execute_reply": "2024-08-12T19:01:08.459864Z" + "iopub.execute_input": "2024-08-15T19:34:30.891037Z", + "iopub.status.busy": "2024-08-15T19:34:30.890849Z", + "iopub.status.idle": "2024-08-15T19:34:30.895162Z", + "shell.execute_reply": "2024-08-15T19:34:30.894690Z" }, "nbsphinx": "hidden" }, @@ -417,10 +417,10 @@ "id": "df5a0f59", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.462528Z", - "iopub.status.busy": "2024-08-12T19:01:08.462216Z", - "iopub.status.idle": "2024-08-12T19:01:08.707993Z", - "shell.execute_reply": "2024-08-12T19:01:08.707383Z" + "iopub.execute_input": "2024-08-15T19:34:30.896992Z", + "iopub.status.busy": "2024-08-15T19:34:30.896820Z", + "iopub.status.idle": "2024-08-15T19:34:31.103439Z", + "shell.execute_reply": "2024-08-15T19:34:31.102838Z" } }, "outputs": [ @@ -456,10 +456,10 @@ "id": "7af78a8a", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.710301Z", - "iopub.status.busy": "2024-08-12T19:01:08.709890Z", - "iopub.status.idle": "2024-08-12T19:01:08.714510Z", - "shell.execute_reply": "2024-08-12T19:01:08.713939Z" + "iopub.execute_input": "2024-08-15T19:34:31.105761Z", + "iopub.status.busy": "2024-08-15T19:34:31.105405Z", + "iopub.status.idle": "2024-08-15T19:34:31.109654Z", + "shell.execute_reply": "2024-08-15T19:34:31.109211Z" } }, "outputs": [], @@ -477,10 +477,10 @@ "id": "9556c624", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.716693Z", - "iopub.status.busy": "2024-08-12T19:01:08.716512Z", - "iopub.status.idle": "2024-08-12T19:01:08.722640Z", - "shell.execute_reply": "2024-08-12T19:01:08.722141Z" + "iopub.execute_input": "2024-08-15T19:34:31.111680Z", + "iopub.status.busy": "2024-08-15T19:34:31.111346Z", + "iopub.status.idle": "2024-08-15T19:34:31.117049Z", + "shell.execute_reply": "2024-08-15T19:34:31.116575Z" } }, "outputs": [], @@ -527,10 +527,10 @@ "id": "3c2f1ccc", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.724891Z", - "iopub.status.busy": "2024-08-12T19:01:08.724714Z", - "iopub.status.idle": "2024-08-12T19:01:08.727505Z", - "shell.execute_reply": "2024-08-12T19:01:08.726971Z" + "iopub.execute_input": "2024-08-15T19:34:31.119084Z", + "iopub.status.busy": "2024-08-15T19:34:31.118908Z", + "iopub.status.idle": "2024-08-15T19:34:31.121735Z", + "shell.execute_reply": "2024-08-15T19:34:31.121157Z" } }, "outputs": [], @@ -545,10 +545,10 @@ "id": "7e1b7860", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:08.729639Z", - "iopub.status.busy": "2024-08-12T19:01:08.729330Z", - "iopub.status.idle": "2024-08-12T19:01:17.979569Z", - "shell.execute_reply": "2024-08-12T19:01:17.978818Z" + "iopub.execute_input": "2024-08-15T19:34:31.123820Z", + "iopub.status.busy": "2024-08-15T19:34:31.123507Z", + "iopub.status.idle": "2024-08-15T19:34:39.956092Z", + "shell.execute_reply": "2024-08-15T19:34:39.955453Z" } }, "outputs": [], @@ -572,10 +572,10 @@ "id": "f407bd69", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:17.983017Z", - "iopub.status.busy": "2024-08-12T19:01:17.982303Z", - "iopub.status.idle": "2024-08-12T19:01:17.990196Z", - "shell.execute_reply": "2024-08-12T19:01:17.989677Z" + "iopub.execute_input": "2024-08-15T19:34:39.958974Z", + "iopub.status.busy": "2024-08-15T19:34:39.958342Z", + "iopub.status.idle": "2024-08-15T19:34:39.965529Z", + "shell.execute_reply": "2024-08-15T19:34:39.965069Z" } }, "outputs": [ @@ -678,10 +678,10 @@ "id": "f7385336", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:17.992517Z", - "iopub.status.busy": "2024-08-12T19:01:17.992064Z", - "iopub.status.idle": "2024-08-12T19:01:17.996208Z", - "shell.execute_reply": "2024-08-12T19:01:17.995603Z" + "iopub.execute_input": "2024-08-15T19:34:39.967484Z", + "iopub.status.busy": "2024-08-15T19:34:39.967308Z", + "iopub.status.idle": "2024-08-15T19:34:39.971426Z", + "shell.execute_reply": "2024-08-15T19:34:39.970996Z" } }, "outputs": [], @@ -696,10 +696,10 @@ "id": "59fc3091", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:17.998537Z", - "iopub.status.busy": "2024-08-12T19:01:17.998176Z", - "iopub.status.idle": "2024-08-12T19:01:18.001616Z", - "shell.execute_reply": "2024-08-12T19:01:18.001073Z" + "iopub.execute_input": "2024-08-15T19:34:39.973295Z", + "iopub.status.busy": "2024-08-15T19:34:39.973123Z", + "iopub.status.idle": "2024-08-15T19:34:39.976540Z", + "shell.execute_reply": "2024-08-15T19:34:39.976080Z" } }, "outputs": [ @@ -734,10 +734,10 @@ "id": "00949977", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:18.003807Z", - "iopub.status.busy": "2024-08-12T19:01:18.003450Z", - "iopub.status.idle": "2024-08-12T19:01:18.006493Z", - "shell.execute_reply": "2024-08-12T19:01:18.006035Z" + "iopub.execute_input": "2024-08-15T19:34:39.978376Z", + "iopub.status.busy": "2024-08-15T19:34:39.978203Z", + "iopub.status.idle": "2024-08-15T19:34:39.981324Z", + "shell.execute_reply": "2024-08-15T19:34:39.980848Z" } }, "outputs": [], @@ -756,10 +756,10 @@ "id": "b6c1ae3a", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:18.008664Z", - "iopub.status.busy": "2024-08-12T19:01:18.008301Z", - "iopub.status.idle": "2024-08-12T19:01:18.017065Z", - "shell.execute_reply": "2024-08-12T19:01:18.016561Z" + "iopub.execute_input": "2024-08-15T19:34:39.983100Z", + "iopub.status.busy": "2024-08-15T19:34:39.982931Z", + "iopub.status.idle": "2024-08-15T19:34:39.990877Z", + "shell.execute_reply": "2024-08-15T19:34:39.990423Z" } }, "outputs": [ @@ -883,10 +883,10 @@ "id": "9131d82d", "metadata": { "execution": { - 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    3. Use cleanlab to find label issues

    -
    +
    -
    +
    @@ -891,7 +891,7 @@

    Classes which are commonly mislabeled overall

    -
    +
    @@ -1140,7 +1140,7 @@

    Get label quality scores

    -
    +

    Beyond scoring the overall label quality of each image, the above method produces a (0 to 1) quality score for each pixel. We can apply a thresholding function to these scores in order to extract the same style True or False mask as find_label_issues().

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"2024-08-15T19:34:49.673313Z", + "iopub.status.busy": "2024-08-15T19:34:49.672897Z", + "iopub.status.idle": "2024-08-15T19:34:52.071821Z", + "shell.execute_reply": "2024-08-15T19:34:52.071128Z" } }, "outputs": [], @@ -79,10 +79,10 @@ "id": "58fd4c55", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:01:31.385281Z", - "iopub.status.busy": "2024-08-12T19:01:31.385088Z", - "iopub.status.idle": "2024-08-12T19:02:51.389352Z", - "shell.execute_reply": "2024-08-12T19:02:51.388576Z" + "iopub.execute_input": "2024-08-15T19:34:52.074238Z", + "iopub.status.busy": "2024-08-15T19:34:52.074048Z", + "iopub.status.idle": "2024-08-15T19:35:55.656911Z", + "shell.execute_reply": "2024-08-15T19:35:55.656253Z" } }, "outputs": [], @@ -97,10 +97,10 @@ "id": "439b0305", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:02:51.392413Z", - "iopub.status.busy": "2024-08-12T19:02:51.391923Z", - "iopub.status.idle": "2024-08-12T19:02:52.823997Z", - "shell.execute_reply": "2024-08-12T19:02:52.823349Z" + "iopub.execute_input": "2024-08-15T19:35:55.659501Z", + "iopub.status.busy": "2024-08-15T19:35:55.659124Z", + "iopub.status.idle": "2024-08-15T19:35:57.039279Z", + "shell.execute_reply": "2024-08-15T19:35:57.038726Z" }, "nbsphinx": "hidden" }, @@ -111,7 +111,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -137,10 +137,10 @@ "id": "a1349304", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:02:52.826500Z", - "iopub.status.busy": "2024-08-12T19:02:52.826198Z", - "iopub.status.idle": "2024-08-12T19:02:52.829390Z", - "shell.execute_reply": "2024-08-12T19:02:52.828941Z" + "iopub.execute_input": "2024-08-15T19:35:57.041670Z", + "iopub.status.busy": "2024-08-15T19:35:57.041307Z", + "iopub.status.idle": "2024-08-15T19:35:57.044385Z", + "shell.execute_reply": "2024-08-15T19:35:57.043906Z" } }, "outputs": [], @@ -203,10 +203,10 @@ "id": "07dc5678", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:02:52.831431Z", - "iopub.status.busy": "2024-08-12T19:02:52.831252Z", - "iopub.status.idle": "2024-08-12T19:02:52.835175Z", - "shell.execute_reply": "2024-08-12T19:02:52.834636Z" + "iopub.execute_input": "2024-08-15T19:35:57.046467Z", + "iopub.status.busy": "2024-08-15T19:35:57.046137Z", + "iopub.status.idle": "2024-08-15T19:35:57.049837Z", + "shell.execute_reply": "2024-08-15T19:35:57.049398Z" } }, "outputs": [ @@ -247,10 +247,10 @@ "id": "25ebe22a", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:02:52.837164Z", - "iopub.status.busy": "2024-08-12T19:02:52.836866Z", - "iopub.status.idle": "2024-08-12T19:02:52.840479Z", - "shell.execute_reply": "2024-08-12T19:02:52.839931Z" + "iopub.execute_input": "2024-08-15T19:35:57.052038Z", + "iopub.status.busy": "2024-08-15T19:35:57.051633Z", + "iopub.status.idle": "2024-08-15T19:35:57.055264Z", + "shell.execute_reply": "2024-08-15T19:35:57.054722Z" } }, "outputs": [ @@ -290,10 +290,10 @@ "id": "3faedea9", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:02:52.842525Z", - "iopub.status.busy": "2024-08-12T19:02:52.842229Z", - "iopub.status.idle": "2024-08-12T19:02:52.845060Z", - "shell.execute_reply": "2024-08-12T19:02:52.844585Z" + "iopub.execute_input": "2024-08-15T19:35:57.057168Z", + "iopub.status.busy": "2024-08-15T19:35:57.056847Z", + "iopub.status.idle": "2024-08-15T19:35:57.059727Z", + "shell.execute_reply": "2024-08-15T19:35:57.059173Z" } }, "outputs": [], @@ -333,17 +333,17 @@ "id": "2c2ad9ad", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:02:52.847164Z", - "iopub.status.busy": "2024-08-12T19:02:52.846766Z", - "iopub.status.idle": "2024-08-12T19:03:30.979394Z", - "shell.execute_reply": "2024-08-12T19:03:30.978678Z" + "iopub.execute_input": "2024-08-15T19:35:57.061621Z", + "iopub.status.busy": "2024-08-15T19:35:57.061444Z", + "iopub.status.idle": "2024-08-15T19:36:34.714746Z", + "shell.execute_reply": "2024-08-15T19:36:34.714106Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "39affc08e5f34107aecde4923e369b00", + "model_id": "09611a74db304abaaccbb482d8c4d5d8", "version_major": 2, "version_minor": 0 }, @@ -357,7 +357,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "17e6f9789f2940c89eb85d25b9f2b5ff", + "model_id": "4fd2b743a1234921975c3fb49e129d95", "version_major": 2, "version_minor": 0 }, @@ -400,10 +400,10 @@ "id": "95dc7268", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:03:30.982173Z", - "iopub.status.busy": "2024-08-12T19:03:30.981956Z", - "iopub.status.idle": "2024-08-12T19:03:31.426214Z", - "shell.execute_reply": "2024-08-12T19:03:31.425623Z" + "iopub.execute_input": "2024-08-15T19:36:34.717479Z", + "iopub.status.busy": "2024-08-15T19:36:34.717143Z", + "iopub.status.idle": "2024-08-15T19:36:35.165510Z", + "shell.execute_reply": "2024-08-15T19:36:35.165009Z" } }, "outputs": [ @@ -446,10 +446,10 @@ "id": "57fed473", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:03:31.428570Z", - "iopub.status.busy": "2024-08-12T19:03:31.428224Z", - "iopub.status.idle": "2024-08-12T19:03:34.405754Z", - "shell.execute_reply": "2024-08-12T19:03:34.405232Z" + "iopub.execute_input": "2024-08-15T19:36:35.167769Z", + "iopub.status.busy": "2024-08-15T19:36:35.167422Z", + "iopub.status.idle": "2024-08-15T19:36:38.130756Z", + "shell.execute_reply": "2024-08-15T19:36:38.130157Z" } }, "outputs": [ @@ -519,17 +519,17 @@ "id": "e4a006bd", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:03:34.408101Z", - 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    1. Install required dependencies and download data 
    ---2024-08-12 19:04:36--  https://data.deepai.org/conll2003.zip
-Resolving data.deepai.org (data.deepai.org)... 169.150.249.167, 2400:52e0:1a01::1108:1
-Connecting to data.deepai.org (data.deepai.org)|169.150.249.167|:443... connected.
+--2024-08-15 19:37:39--  https://data.deepai.org/conll2003.zip
+Resolving data.deepai.org (data.deepai.org)... 169.150.236.98, 2400:52e0:1a00::1070:1
+Connecting to data.deepai.org (data.deepai.org)|169.150.236.98|:443... connected.
 HTTP request sent, awaiting response... 200 OK
 Length: 982975 (960K) [application/zip]
 Saving to: ‘conll2003.zip’
 
-conll2003.zip       100%[===================>] 959.94K  5.80MB/s    in 0.2s
+conll2003.zip       100%[===================>] 959.94K  --.-KB/s    in 0.1s
 
-2024-08-12 19:04:37 (5.80 MB/s) - ‘conll2003.zip’ saved [982975/982975]
+2024-08-15 19:37:39 (7.14 MB/s) - ‘conll2003.zip’ saved [982975/982975]
 
 mkdir: cannot create directory ‘data’: File exists
 Archive:  conll2003.zip
@@ -727,16 +727,16 @@ 
    1. Install required dependencies and download data

    diff --git a/master/tutorials/token_classification.ipynb b/master/tutorials/token_classification.ipynb index b937d8f5c..e5bbfa445 100644 --- a/master/tutorials/token_classification.ipynb +++ b/master/tutorials/token_classification.ipynb @@ -75,10 +75,10 @@ "id": "ae8a08e0", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:36.973694Z", - "iopub.status.busy": "2024-08-12T19:04:36.973533Z", - "iopub.status.idle": "2024-08-12T19:04:38.928223Z", - "shell.execute_reply": "2024-08-12T19:04:38.927569Z" + "iopub.execute_input": "2024-08-15T19:37:39.451838Z", + "iopub.status.busy": "2024-08-15T19:37:39.451267Z", + "iopub.status.idle": "2024-08-15T19:37:40.711098Z", + "shell.execute_reply": "2024-08-15T19:37:40.710482Z" } }, "outputs": [ @@ -86,16 +86,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-08-12 19:04:36-- https://data.deepai.org/conll2003.zip\r\n", - "Resolving data.deepai.org (data.deepai.org)... " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "169.150.249.167, 2400:52e0:1a01::1108:1\r\n", - "Connecting to data.deepai.org (data.deepai.org)|169.150.249.167|:443... connected.\r\n" + "--2024-08-15 19:37:39-- https://data.deepai.org/conll2003.zip\r\n", + "Resolving data.deepai.org (data.deepai.org)... 169.150.236.98, 2400:52e0:1a00::1070:1\r\n", + "Connecting to data.deepai.org (data.deepai.org)|169.150.236.98|:443... connected.\r\n" ] }, { @@ -115,16 +108,10 @@ "output_type": "stream", "text": [ "\r", - "conll2003.zip 100%[===================>] 959.94K 5.80MB/s in 0.2s \r\n", + "conll2003.zip 100%[===================>] 959.94K --.-KB/s in 0.1s \r\n", + "\r\n", + "2024-08-15 19:37:39 (7.14 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n", "\r\n", - "2024-08-12 19:04:37 (5.80 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n", - "\r\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ "mkdir: cannot create directory ‘data’: File exists\r\n" ] }, @@ -135,14 +122,7 @@ "Archive: conll2003.zip\r\n", " inflating: data/metadata \r\n", " inflating: data/test.txt \r\n", - " inflating: data/train.txt " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r\n", + " inflating: data/train.txt \r\n", " inflating: data/valid.txt \r\n" ] }, @@ -150,16 +130,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-08-12 19:04:37-- https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n", - "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 54.231.136.129, 16.182.36.201, 3.5.10.169, ...\r\n", - "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|54.231.136.129|:443... " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "connected.\r\n" + "--2024-08-15 19:37:39-- https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n", + "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 52.217.75.76, 3.5.6.127, 52.217.139.217, ...\r\n", + "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|52.217.75.76|:443... connected.\r\n" ] }, { @@ -186,15 +159,7 @@ "output_type": "stream", "text": [ "\r", - "pred_probs.npz 1%[ ] 295.53K 1.20MB/s " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", - "pred_probs.npz 30%[=====> ] 4.92M 10.2MB/s " + "pred_probs.npz 50%[=========> ] 8.18M 37.6MB/s " ] }, { @@ -202,9 +167,9 @@ "output_type": "stream", "text": [ "\r", - "pred_probs.npz 100%[===================>] 16.26M 24.1MB/s in 0.7s \r\n", + "pred_probs.npz 100%[===================>] 16.26M 47.6MB/s in 0.3s \r\n", "\r\n", - "2024-08-12 19:04:38 (24.1 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n", + "2024-08-15 19:37:40 (47.6 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n", "\r\n" ] } @@ -221,10 +186,10 @@ "id": "439b0305", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:38.931095Z", - "iopub.status.busy": "2024-08-12T19:04:38.930692Z", - "iopub.status.idle": "2024-08-12T19:04:40.560281Z", - "shell.execute_reply": "2024-08-12T19:04:40.559629Z" + "iopub.execute_input": "2024-08-15T19:37:40.713604Z", + "iopub.status.busy": "2024-08-15T19:37:40.713237Z", + "iopub.status.idle": "2024-08-15T19:37:42.244060Z", + "shell.execute_reply": "2024-08-15T19:37:42.243504Z" }, "nbsphinx": "hidden" }, @@ -235,7 +200,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@280db6acac455fd07347f9bd9bb8efec2c960500\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -261,10 +226,10 @@ "id": "a1349304", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:40.563056Z", - "iopub.status.busy": "2024-08-12T19:04:40.562726Z", - "iopub.status.idle": "2024-08-12T19:04:40.566447Z", - "shell.execute_reply": "2024-08-12T19:04:40.565965Z" + "iopub.execute_input": "2024-08-15T19:37:42.246581Z", + "iopub.status.busy": "2024-08-15T19:37:42.246114Z", + "iopub.status.idle": "2024-08-15T19:37:42.249536Z", + "shell.execute_reply": "2024-08-15T19:37:42.249089Z" } }, "outputs": [], @@ -314,10 +279,10 @@ "id": "ab9d59a0", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:40.568406Z", - "iopub.status.busy": "2024-08-12T19:04:40.568215Z", - "iopub.status.idle": "2024-08-12T19:04:40.571337Z", - "shell.execute_reply": "2024-08-12T19:04:40.570894Z" + "iopub.execute_input": "2024-08-15T19:37:42.251693Z", + "iopub.status.busy": "2024-08-15T19:37:42.251363Z", + "iopub.status.idle": "2024-08-15T19:37:42.254787Z", + "shell.execute_reply": "2024-08-15T19:37:42.254367Z" }, "nbsphinx": "hidden" }, @@ -335,10 +300,10 @@ "id": "519cb80c", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:40.573600Z", - "iopub.status.busy": "2024-08-12T19:04:40.573107Z", - "iopub.status.idle": "2024-08-12T19:04:49.797790Z", - "shell.execute_reply": "2024-08-12T19:04:49.797189Z" + "iopub.execute_input": "2024-08-15T19:37:42.256850Z", + "iopub.status.busy": "2024-08-15T19:37:42.256520Z", + "iopub.status.idle": "2024-08-15T19:37:51.322045Z", + "shell.execute_reply": "2024-08-15T19:37:51.321484Z" } }, "outputs": [], @@ -412,10 +377,10 @@ "id": "202f1526", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:49.800253Z", - "iopub.status.busy": "2024-08-12T19:04:49.800047Z", - "iopub.status.idle": "2024-08-12T19:04:49.805958Z", - "shell.execute_reply": "2024-08-12T19:04:49.805478Z" + "iopub.execute_input": "2024-08-15T19:37:51.324581Z", + "iopub.status.busy": "2024-08-15T19:37:51.324201Z", + "iopub.status.idle": "2024-08-15T19:37:51.329797Z", + "shell.execute_reply": "2024-08-15T19:37:51.329328Z" }, "nbsphinx": "hidden" }, @@ -455,10 +420,10 @@ "id": "a4381f03", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:49.808179Z", - "iopub.status.busy": "2024-08-12T19:04:49.807741Z", - "iopub.status.idle": "2024-08-12T19:04:50.206957Z", - "shell.execute_reply": "2024-08-12T19:04:50.206380Z" + "iopub.execute_input": "2024-08-15T19:37:51.331779Z", + "iopub.status.busy": "2024-08-15T19:37:51.331449Z", + "iopub.status.idle": "2024-08-15T19:37:51.694028Z", + "shell.execute_reply": "2024-08-15T19:37:51.693526Z" } }, "outputs": [], @@ -495,10 +460,10 @@ "id": "7842e4a3", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:50.209465Z", - "iopub.status.busy": "2024-08-12T19:04:50.209239Z", - "iopub.status.idle": "2024-08-12T19:04:50.214098Z", - "shell.execute_reply": "2024-08-12T19:04:50.213547Z" + "iopub.execute_input": "2024-08-15T19:37:51.696563Z", + "iopub.status.busy": "2024-08-15T19:37:51.696109Z", + "iopub.status.idle": "2024-08-15T19:37:51.700624Z", + "shell.execute_reply": "2024-08-15T19:37:51.700057Z" } }, "outputs": [ @@ -570,10 +535,10 @@ "id": "2c2ad9ad", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:50.216424Z", - "iopub.status.busy": "2024-08-12T19:04:50.216093Z", - "iopub.status.idle": "2024-08-12T19:04:53.028488Z", - "shell.execute_reply": "2024-08-12T19:04:53.027771Z" + "iopub.execute_input": "2024-08-15T19:37:51.702646Z", + "iopub.status.busy": "2024-08-15T19:37:51.702321Z", + "iopub.status.idle": "2024-08-15T19:37:54.357930Z", + "shell.execute_reply": "2024-08-15T19:37:54.357225Z" } }, "outputs": [], @@ -595,10 +560,10 @@ "id": "95dc7268", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:53.031980Z", - "iopub.status.busy": "2024-08-12T19:04:53.030986Z", - "iopub.status.idle": "2024-08-12T19:04:53.035538Z", - "shell.execute_reply": "2024-08-12T19:04:53.035049Z" + "iopub.execute_input": "2024-08-15T19:37:54.361315Z", + "iopub.status.busy": "2024-08-15T19:37:54.360477Z", + "iopub.status.idle": "2024-08-15T19:37:54.364594Z", + "shell.execute_reply": "2024-08-15T19:37:54.364081Z" } }, "outputs": [ @@ -634,10 +599,10 @@ "id": "e13de188", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:53.037496Z", - "iopub.status.busy": "2024-08-12T19:04:53.037328Z", - "iopub.status.idle": "2024-08-12T19:04:53.042801Z", - "shell.execute_reply": "2024-08-12T19:04:53.042346Z" + "iopub.execute_input": "2024-08-15T19:37:54.366654Z", + "iopub.status.busy": "2024-08-15T19:37:54.366321Z", + "iopub.status.idle": "2024-08-15T19:37:54.371850Z", + "shell.execute_reply": "2024-08-15T19:37:54.371414Z" } }, "outputs": [ @@ -815,10 +780,10 @@ "id": "e4a006bd", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:53.044863Z", - "iopub.status.busy": "2024-08-12T19:04:53.044545Z", - "iopub.status.idle": "2024-08-12T19:04:53.071401Z", - "shell.execute_reply": "2024-08-12T19:04:53.070922Z" + "iopub.execute_input": "2024-08-15T19:37:54.373914Z", + "iopub.status.busy": "2024-08-15T19:37:54.373583Z", + "iopub.status.idle": "2024-08-15T19:37:54.399608Z", + "shell.execute_reply": "2024-08-15T19:37:54.399157Z" } }, "outputs": [ @@ -920,10 +885,10 @@ "id": "c8f4e163", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:53.073476Z", - "iopub.status.busy": "2024-08-12T19:04:53.073299Z", - "iopub.status.idle": "2024-08-12T19:04:53.077762Z", - "shell.execute_reply": "2024-08-12T19:04:53.077215Z" + "iopub.execute_input": "2024-08-15T19:37:54.401718Z", + "iopub.status.busy": "2024-08-15T19:37:54.401393Z", + "iopub.status.idle": "2024-08-15T19:37:54.405238Z", + "shell.execute_reply": "2024-08-15T19:37:54.404714Z" } }, "outputs": [ @@ -997,10 +962,10 @@ "id": "db0b5179", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:53.079859Z", - "iopub.status.busy": "2024-08-12T19:04:53.079550Z", - "iopub.status.idle": "2024-08-12T19:04:54.603315Z", - "shell.execute_reply": "2024-08-12T19:04:54.602668Z" + "iopub.execute_input": "2024-08-15T19:37:54.407260Z", + "iopub.status.busy": "2024-08-15T19:37:54.406920Z", + "iopub.status.idle": "2024-08-15T19:37:55.884011Z", + "shell.execute_reply": "2024-08-15T19:37:55.883471Z" } }, "outputs": [ @@ -1172,10 +1137,10 @@ "id": "a18795eb", "metadata": { "execution": { - "iopub.execute_input": "2024-08-12T19:04:54.605501Z", - "iopub.status.busy": "2024-08-12T19:04:54.605297Z", - "iopub.status.idle": "2024-08-12T19:04:54.609527Z", - "shell.execute_reply": "2024-08-12T19:04:54.609049Z" + "iopub.execute_input": "2024-08-15T19:37:55.886211Z", + "iopub.status.busy": "2024-08-15T19:37:55.885873Z", + "iopub.status.idle": "2024-08-15T19:37:55.890341Z", + "shell.execute_reply": "2024-08-15T19:37:55.889924Z" }, "nbsphinx": "hidden" }, diff --git a/versioning.js b/versioning.js index bc6dead51..6bba319c6 100644 --- a/versioning.js +++ b/versioning.js @@ -1,4 +1,4 @@ var Version = { version_number: "v2.6.6", - commit_hash: "5f4d3cc7dcef17f6e59ac5fd18eec27d6e37134b", + commit_hash: "280db6acac455fd07347f9bd9bb8efec2c960500", }; \ No newline at end of file

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