learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
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: 30

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
0.8861	1.0	330	0.5810	0.5413	0.5217	0.5313
0.5143	2.0	660	0.5206	0.5377	0.6076	0.5705
0.4166	3.0	990	0.5114	0.5639	0.6173	0.5894
0.3444	4.0	1320	0.5223	0.5780	0.6301	0.6029
0.2877	5.0	1650	0.5433	0.5727	0.6396	0.6043
0.24	6.0	1980	0.5703	0.5989	0.6287	0.6134
0.2021	7.0	2310	0.6136	0.5731	0.6354	0.6027
0.1716	8.0	2640	0.6271	0.5924	0.6298	0.6105
0.1469	9.0	2970	0.6589	0.5857	0.6296	0.6068
0.125	10.0	3300	0.7028	0.5856	0.6355	0.6095
0.1076	11.0	3630	0.7385	0.5862	0.6378	0.6109
0.0942	12.0	3960	0.7678	0.5911	0.6348	0.6122
0.0817	13.0	4290	0.7819	0.5900	0.6334	0.6110
0.0718	14.0	4620	0.8135	0.5837	0.6390	0.6101
0.0639	15.0	4950	0.8489	0.5906	0.6339	0.6115
0.0566	16.0	5280	0.8729	0.5819	0.6416	0.6103
0.0499	17.0	5610	0.8930	0.5876	0.6379	0.6117
0.0447	18.0	5940	0.9162	0.5895	0.6383	0.6129
0.0403	19.0	6270	0.9366	0.5925	0.6340	0.6126
0.0365	20.0	6600	0.9515	0.5918	0.6345	0.6124
0.0331	21.0	6930	0.9742	0.5879	0.6393	0.6125
0.03	22.0	7260	0.9920	0.5860	0.6375	0.6107
0.0277	23.0	7590	1.0081	0.5916	0.6389	0.6143
0.025	24.0	7920	1.0272	0.5887	0.6370	0.6119
0.0232	25.0	8250	1.0267	0.5959	0.6325	0.6137
0.0216	26.0	8580	1.0528	0.5907	0.6382	0.6135
0.0209	27.0	8910	1.0533	0.5925	0.6385	0.6146
0.0195	28.0	9240	1.0617	0.5913	0.6398	0.6146
0.0186	29.0	9570	1.0668	0.5936	0.6379	0.6150
0.018	30.0	9900	1.0704	0.5926	0.6403	0.6156

cp-gustavo/test-biobert-finetuned-ner-medmentions

test-biobert-finetuned-ner-medmentions