learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.0197	2.64	100	0.5256	0.4831	0.4319	0.4561	0.8719
0.1435	5.2667	200	0.1149	0.9453	0.9329	0.9390	0.9744
0.0655	7.9067	300	0.0673	0.9473	0.9688	0.9579	0.9809
0.0441	10.5333	400	0.0754	0.9708	0.9693	0.9700	0.9832
0.0236	13.16	500	0.0790	0.9697	0.9772	0.9734	0.9832
0.0171	15.8	600	0.0849	0.9670	0.9797	0.9733	0.9835

dandankim/distilbert-ner-improved

distilbert-ner-improved