learning_rate: 0.001
train_batch_size: 1
eval_batch_size: 6
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
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_steps: 100
num_epochs: 5
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Cer	Wer
0.3852	0.6231	200	0.9490	0.1866	0.5388
0.3834	1.2461	400	0.8982	0.1913	0.5373
0.3539	1.8692	600	0.9107	0.1877	0.5265
0.3641	2.4922	800	0.9277	0.1873	0.5250
0.3281	3.1153	1000	0.9339	0.1895	0.5360
0.3245	3.7383	1200	0.9323	0.1871	0.5261
0.2834	4.3614	1400	0.9389	0.1841	0.5205
0.278	4.9844	1600	0.9357	0.1848	0.5245

ctaguchi/ssc-meh-mms-model-mix-adapt-max2

ssc-meh-mms-model-mix-adapt-max2