library_name: transformers
tags: []
wandb: - 0.003 MB of 0.003 MB uploaded
wandb: \ 0.003 MB of 0.003 MB uploaded
wandb:
wandb:
wandb: Run history:
wandb: eval/loss █▅▅▄▃▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
wandb: eval/runtime ▆▃▃▁▂▅█▅▄▄▄▄▄▄▅▄▆▄▂▅▃▄▆▆▂▆▅
wandb: eval/samples_per_second ▃▆▆█▇▄▁▄▅▅▅▅▅▅▄▅▃▅▇▄▆▅▃▃▇▃▄
wandb: eval/steps_per_second ▃▆▆█▇▄▁▄▄▄▅▅▄▅▄▅▃▆▇▃▆▅▃▃▇▃▄
wandb: train/epoch ▁▁▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▅▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇███
wandb: train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▇▇▇▇▇███
wandb: train/grad_norm ▇▂▂▂▁▃█▃▂▁▃▂▃▂▁▂▃▃▄▃▂▃▃▃▄▂▃▃▄▃▂▃▃▃▃▄▄▅▄▃
wandb: train/learning_rate ███▇▇▇▇▇▇▆▆▆▆▆▅▅▅▅▅▅▄▄▄▄▄▄▃▃▃▃▃▂▂▂▂▂▂▁▁▁
wandb: train/loss █▃▃▃▁▄▂▂▃▁▃▂▂▂▁▃▂▂▁▃▂▂▂▁▃▂▂▂▁▃▂▂▂▃▁▂▂▁▃▁
wandb:
wandb: Run summary:
wandb: eval/loss 0.92221
wandb: eval/runtime 93.6611
wandb: eval/samples_per_second 3.587
wandb: eval/steps_per_second 1.196
wandb: total_flos 2.952274602780672e+16
wandb: train/epoch 2.46201
wandb: train/global_step 810
wandb: train/grad_norm 0.81067
wandb: train/learning_rate 3e-05
wandb: train/loss 0.7747
wandb: train_loss 1.05936
wandb: train_runtime 8326.639
wandb: train_samples_per_second 1.58
wandb: train_steps_per_second 0.198
training_arguments = SFTConfig(
output_dir=new_model,
run_name="fine_tune_ocr_correction",
per_device_train_batch_size=4,
per_device_eval_batch_size=3,
gradient_accumulation_steps=4,
optim="paged_adamw_32bit",
num_train_epochs=5,
eval_strategy="steps",
eval_steps=30, # normally 10 steps, but our dataset is small
save_steps=30,
logging_steps=20, # Log progress every 20 steps
warmup_steps=10,
logging_strategy="steps",
learning_rate=5e-5,
fp16=use_fp16,
bf16=use_bf16,
group_by_length=True,
report_to="wandb",
max_seq_length=1220,
save_strategy="steps",
dataset_text_field="text",
load_best_model_at_end = True
)
Llama-3.2-post-ocr-synthetic-data-2 (test on synth data, training on full corpus).json
Average PCIS: -0.06044562
Average Dataset CER: 0.09836092
Average Model CER: 0.15258657
Average Dataset WER: 0.21986217
Average Model WER: 0.80281940
Llama-3.2-post-ocr-synthetic-data-2 (test on real data, training on full corpus).json
Average PCIS: -0.00842250
Average Dataset CER: 0.01391665
Average Model CER: 0.02204702
Average Dataset WER: 0.06207812
Average Model WER: 0.10260357
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