目前训练日志中，训练性能指标如何分析呢？

[tensorflowt]

Reminder

• I have read the README and searched the existing issues.

System Info

目前我这边在a800880GB机器上训练llama3-8b模型，我这边的训练日志如下：

这里面每秒训练样本数只有40个，这个样本数和tokens如何对应呢？如何是40个tokens那就很慢呀！如果是cutoff_len*10=409600又很大感觉也不对！这块帮忙分析一下？

Reproduction

我的配置文件如下：

model

model_name_or_path: LLM-Research/Meta-Llama-3-8B-Instruct
cache_dir: /worker

method

stage: sft
do_train: true
finetuning_type: lora
lora_target: all

dataset

dataset: identity,alpaca_en_demo
template: llama3
cutoff_len: 1024
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16

output

output_dir: /data/saves/llama3-8b/lora/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true

train

per_device_train_batch_size: 8
gradient_accumulation_steps: 8
learning_rate: 1.0e-4
num_train_epochs: 5.0
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: true
ddp_timeout: 180000000

eval

val_size: 0.1
per_device_eval_batch_size: 1
eval_strategy: steps
eval_steps: 500

Expected behavior

No response

Others

No response