learning_rate: 1e-05
train_batch_size: 4
eval_batch_size: 4
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: 5

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4181	0.1667	30	1.0830	0.6180
1.0256	0.3333	60	0.9486	0.6292
0.8829	0.5	90	0.8497	0.6180
0.9786	0.6667	120	0.8237	0.6180
0.9139	0.8333	150	0.8359	0.6180
0.8676	1.0	180	0.8173	0.6180
0.9303	1.1667	210	0.9327	0.4719
0.8582	1.3333	240	0.8055	0.6180
0.7649	1.5	270	0.8192	0.6629
0.7704	1.6667	300	0.7474	0.6292
0.707	1.8333	330	0.7991	0.6517
0.7365	2.0	360	0.8396	0.6404
0.6829	2.1667	390	0.8587	0.6292
0.7915	2.3333	420	0.7690	0.6067
0.6379	2.5	450	0.7855	0.6180
0.6395	2.6667	480	0.8459	0.6180
0.7959	2.8333	510	0.8334	0.6067
0.6763	3.0	540	0.7708	0.6292
0.5994	3.1667	570	0.8023	0.5955
0.6019	3.3333	600	0.7704	0.6517
0.5012	3.5	630	0.7716	0.6629
0.5491	3.6667	660	0.8075	0.6629
0.5157	3.8333	690	0.8084	0.6292
0.6399	4.0	720	0.9289	0.5843
0.5434	4.1667	750	0.7897	0.6742
0.4594	4.3333	780	0.8102	0.6742
0.5249	4.5	810	0.8528	0.6854
0.3474	4.6667	840	0.8637	0.6854
0.5049	4.8333	870	0.8847	0.6742
0.4422	5.0	900	0.8530	0.6517

TakalaWang/bert-finetuned

bert-finetuned