learning_rate: 5e-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: 10

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision
0.3524	1.0	500	0.6161	0.867	0.8508	0.867	0.8553
0.2878	2.0	1000	0.5404	0.882	0.8706	0.882	0.8739
0.1682	3.0	1500	0.7048	0.879	0.8684	0.879	0.8699
0.1006	4.0	2000	0.7590	0.877	0.8610	0.877	0.8698
0.0421	5.0	2500	0.7716	0.878	0.8742	0.878	0.8722
0.0205	6.0	3000	0.8432	0.887	0.8804	0.887	0.8798
0.0294	7.0	3500	0.8998	0.884	0.8661	0.884	0.8837
0.0099	8.0	4000	0.9366	0.882	0.8746	0.882	0.8739
0.0046	9.0	4500	0.9346	0.882	0.8789	0.882	0.8771
0.0028	10.0	5000	0.9742	0.878	0.8729	0.878	0.8709

jco1/results_bert_full

results_bert_full