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tags language widget datasets co2_eq_emissions
text-classification
en
text
Oh, the tragedy!
yigitkucuk/sentimentale-dataset
emissions
0.7402856123778213

Validation Metrics

  • Loss: 0.576
  • Accuracy: 0.827
  • Macro F1: 0.711
  • Micro F1: 0.827
  • Weighted F1: 0.827
  • Macro Precision: 0.708
  • Micro Precision: 0.827
  • Weighted Precision: 0.828
  • Macro Recall: 0.716
  • Micro Recall: 0.827
  • Weighted Recall: 0.827
  • Problem type: Multi-class Classification
  • CO2 Emissions (in grams): 0.7403
  • Model ID: 3099088026

Use with Python API

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("yigitkucuk/Sentimentale", use_auth_token=True)

inputs = tokenizer("Oh, the tragedy!", return_tensors="pt")

outputs = model(**inputs)

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A multi-class text-classification model that evaluates the sentiment in poetic text prompts.

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