learning_rate: 0.0005
train_batch_size: 16
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
lr_scheduler_warmup_ratio: 0.2
num_epochs: 60.0
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
2875.4683	1.0	3628	287.1173	0.5699	0.1733
758.2716	2.0	7256	272.0594	0.4882	0.1551
644.8381	3.0	10884	290.3244	0.5062	0.1729
609.5405	4.0	14512	257.9622	0.5174	0.1867
606.3339	5.0	18140	296.2997	0.5668	0.2280
619.5554	6.0	21768	324.2591	0.5901	0.2188
646.4168	7.0	25396	341.2834	0.5953	0.2440
667.3437	8.0	29024	361.0744	0.6283	0.2255
693.7482	9.0	32652	364.4579	0.6597	0.2685
733.3208	10.0	36280	409.5368	0.7001	0.2802
780.5633	11.0	39908	410.3908	0.7154	0.2849
813.6104	12.0	43536	419.5198	0.7614	0.3089

Priyanship/base_sami_22k_cont_pt_ftpseudo_wr20

base_sami_22k_cont_pt_ftpseudo_wr20