learning_rate: 0.0003
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: 10
num_epochs: 30
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Cer
86.7857	1.0	10	13.0096	0.9930
64.0349	2.0	20	5.7889	1.0
20.8761	3.0	30	4.3652	1.0
12.3363	4.0	40	3.8773	1.0
11.0137	5.0	50	3.7471	1.0
10.7147	6.0	60	3.6982	1.0
10.5702	7.0	70	3.6885	1.0
10.1350	8.0	80	3.6772	1.0
10.7296	9.0	90	3.6753	1.0
10.0155	10.0	100	3.6693	1.0
23.2533	11.0	110	3.6945	1.0
11.0381	12.0	120	3.6739	1.0
10.8187	13.0	130	3.6736	1.0
10.4372	14.0	140	3.6692	1.0
10.3977	15.0	150	3.6721	1.0
10.1144	16.0	160	3.6679	1.0
10.2825	17.0	170	3.6669	1.0
10.4510	18.0	180	3.6651	1.0
10.1287	19.0	190	3.6654	1.0
10.1370	20.0	200	3.6608	1.0
10.3325	21.0	210	3.6639	1.0
10.5143	22.0	220	3.6630	1.0
10.3311	23.0	230	3.6666	1.0
10.4097	24.0	240	3.6611	1.0
13.4818	25.0	250	3.6602	1.0
13.6625	26.0	260	3.6586	1.0
10.1651	27.0	270	3.6568	1.0
10.3636	28.0	280	3.6508	1.0
13.1884	29.0	290	3.6498	1.0
9.9916	30.0	300	3.6497	1.0

ctaguchi/xlsr53

xlsr53