learning_rate: 0.001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.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: 100
num_epochs: 30
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Cer	Wer
1.8351	3.2810	200	1.3899	0.1624	0.5561
1.5048	6.5620	400	1.2824	0.1444	0.4732
1.5952	9.8430	600	1.2806	0.1387	0.4533
0.7156	13.1157	800	1.5784	0.1426	0.4701
0.7436	16.3967	1000	1.3450	0.1473	0.4680
2.1968	19.6777	1200	1.6456	0.5245	0.9318
2.8915	22.9587	1400	2.7871	0.7356	0.9874
3.9703	26.2314	1600	3.8258	0.8417	1.0010
4.0352	29.5124	1800	3.9548	0.9538	1.0010

ctaguchi/ssc-ush-mms-model-mix-adapt-max

ssc-ush-mms-model-mix-adapt-max