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 0.96995
wandb:             eval/runtime 50.348
wandb:  eval/samples_per_second 6.674
wandb:    eval/steps_per_second 2.225
wandb:               total_flos 2.892717018533069e+16
wandb:              train/epoch 2.46201
wandb:        train/global_step 810
wandb:          train/grad_norm 1.0378
wandb:      train/learning_rate 3e-05
wandb:               train/loss 0.3923
wandb:               train_loss 0.67611
wandb:            train_runtime 3867.4895
wandb: train_samples_per_second 3.403
wandb:   train_steps_per_second 0.425

training_arguments = SFTConfig(
    output_dir=new_model,
    run_name="fine_tune_ocr_correction",
    per_device_train_batch_size=2, # or 8 
    per_device_eval_batch_size=3,
    gradient_accumulation_steps=4,
    optim="paged_adamw_32bit",
    num_train_epochs=5, 
    eval_strategy="steps",
    eval_steps=30,  
    save_steps=30,
    logging_steps=10,  
    warmup_steps=10,
    logging_strategy="steps",
    learning_rate= 5e-5, #2e-4, 
    fp16=use_fp16, 
    bf16=use_bf16,  
    group_by_length=True,
    report_to="wandb",
    max_seq_length=1220,
    save_strategy="steps",
    dataset_text_field="text",
    max_grad_norm=0.3,
    warmup_ratio=0.03,
    load_best_model_at_end = True
)

Llama-3.2-3B-ocr-correction-3-instruction-corrected-mixed-data-real-evaluation.json
Average PCIS: -0.00617385
Average Dataset CER: 0.01391665
Average Model CER: 0.01977127
Average Dataset WER: 0.06207812
Average Model WER: 0.08723665

Llama-3.2-3B-ocr-correction-3-instruction-corrected-mixed-data-synth-evaluation.json
Average PCIS: -0.10465669
Average Dataset CER: 0.09836092
Average Model CER: 0.19205506
Average Dataset WER: 0.21986217
Average Model WER: 1.01686689

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