learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 40

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	240	0.2967	0.6682	0.6905	0.6791	0.9113
No log	2.0	480	0.2534	0.7135	0.7351	0.7241	0.9210
0.3367	3.0	720	0.2390	0.7477	0.7281	0.7378	0.9236
0.3367	4.0	960	0.2386	0.7335	0.7462	0.7398	0.9235
0.1877	5.0	1200	0.2473	0.7302	0.7597	0.7446	0.9243
0.1877	6.0	1440	0.2435	0.7449	0.7477	0.7463	0.9261
0.1508	7.0	1680	0.2535	0.7251	0.7712	0.7474	0.9246
0.1508	8.0	1920	0.2564	0.7331	0.7604	0.7465	0.9254
0.1206	9.0	2160	0.2642	0.7435	0.7481	0.7458	0.9256
0.1206	10.0	2400	0.2720	0.7536	0.7415	0.7475	0.9264
0.0984	11.0	2640	0.2866	0.7462	0.7431	0.7446	0.9254
0.0984	12.0	2880	0.2982	0.7332	0.7561	0.7445	0.9250
0.08	13.0	3120	0.3123	0.7289	0.7584	0.7434	0.9252
0.08	14.0	3360	0.3167	0.7239	0.7633	0.7430	0.9237
0.0658	15.0	3600	0.3238	0.7408	0.7499	0.7453	0.9252

grazh/biomedical-ner-all-finetuned-ner-combined-v1

biomedical-ner-all-finetuned-ner-combined-v1