learning_rate: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 1337
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
3.0396	0.9970	500	3.0211	1.0	0.9481
1.417	1.9930	1000	1.1934	0.8057	0.3569
1.2214	2.9890	1500	1.0721	0.6921	0.3182
1.2123	3.9850	2000	1.0590	0.6543	0.3205
1.1298	4.9811	2500	1.0206	0.6191	0.3044
1.1262	5.9771	3000	1.0117	0.6080	0.2961
1.0795	6.9731	3500	1.0168	0.5907	0.2934
1.0582	7.9691	4000	0.9936	0.5786	0.2965
1.0456	8.9651	4500	0.9955	0.5679	0.2905
1.0378	9.9611	5000	0.9963	0.5652	0.2894

SudheenK/xlsr300m-korean-ctc

xlsr300m-korean-ctc