learning_rate: 2e-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: 3

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7551	0.0322	100	0.4489	0.9012
0.3977	0.0644	200	0.5959	0.8943
0.3608	0.0966	300	0.2267	0.9258
0.3092	0.1287	400	0.1801	0.9374
0.1932	0.1609	500	0.1921	0.9562
0.1405	0.1931	600	0.2487	0.9573
0.3093	0.2253	700	0.1245	0.9573
0.1804	0.2575	800	0.1496	0.9602
0.1717	0.2897	900	0.1923	0.9573
0.1986	0.3219	1000	0.4235	0.9167
0.1786	0.3540	1100	0.1436	0.9591
0.1563	0.3862	1200	0.2635	0.9468
0.188	0.4184	1300	0.1891	0.9540
0.137	0.4506	1400	0.2017	0.9348
0.1438	0.4828	1500	0.1510	0.9660
0.1241	0.5150	1600	0.2152	0.9551
0.1793	0.5472	1700	0.1861	0.9602

EndOfLe/fine_tuned_hswag_callback10

fine_tuned_hswag_callback10