learning_rate: 0.0003
train_batch_size: 2
eval_batch_size: 6
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
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: 5
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Cer	Wer
0.25	0.5944	200	0.8255	0.2102	0.7596
0.217	1.1872	400	0.8573	0.2098	0.7456
0.1829	1.7816	600	0.8578	0.2071	0.7451
0.1507	2.3744	800	0.8909	0.2013	0.7319
0.1311	2.9688	1000	0.9180	0.1977	0.7385
0.0985	3.5617	1200	0.9911	0.1988	0.7200
0.083	4.1545	1400	1.0063	0.1898	0.7127
0.0642	4.7489	1600	1.0445	0.1910	0.7159

ctaguchi/ssc-ruc-xlsr300m-model-mix-adapt-max-lowlr

ssc-ruc-xlsr300m-model-mix-adapt-max-lowlr