learning_rate: 2e-05
train_batch_size: 24
eval_batch_size: 24
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
0.3459	0.1083	100	0.1297	0.9602
0.1385	0.2167	200	0.0771	0.9805
0.0918	0.3250	300	0.0951	0.9825
0.1103	0.4334	400	0.0834	0.9813
0.0943	0.5417	500	0.0607	0.9821
0.0692	0.6501	600	0.0714	0.9866
0.0584	0.7584	700	0.0607	0.9858
0.0599	0.8667	800	0.0531	0.9874
0.0672	0.9751	900	0.0312	0.9915
0.0086	1.0834	1000	0.0494	0.9919
0.0084	1.1918	1100	0.0621	0.9890
0.0225	1.3001	1200	0.0433	0.9927
0.0146	1.4085	1300	0.0684	0.9870
0.0126	1.5168	1400	0.0960	0.9878
0.0143	1.6251	1500	0.0454	0.9927
0.0081	1.7335	1600	0.0671	0.9907
0.0064	1.8418	1700	0.0526	0.9919
0.0007	1.9502	1800	0.0458	0.9931
0.003	2.0585	1900	0.0523	0.9931

EndLessTime/fine_tuned_cmv_callback10

fine_tuned_cmv_callback10