learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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: 1000
num_epochs: 15
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer
9.7238	0.9434	400	4.3969	1.0000
3.7833	1.8868	800	3.4483	1.0000
3.407	2.8302	1200	3.3647	1.0000
3.2531	3.7736	1600	2.6273	1.0000
2.3162	4.7170	2000	1.6377	0.9461
1.7377	5.6604	2400	1.2870	0.7850
1.4824	6.6038	2800	1.0638	0.6756
1.3022	7.5472	3200	0.9677	0.6144
1.2161	8.4906	3600	0.9012	0.5805
1.1507	9.4340	4000	0.8627	0.5556
1.1122	10.3774	4400	0.8179	0.5373
1.0667	11.3208	4800	0.8080	0.5243
1.0605	12.2642	5200	0.7947	0.5131
1.0229	13.2075	5600	0.7955	0.5057
1.0302	14.1509	6000	0.7778	0.5015

pdabo1607/Vietnamese_Wav2Vec_Finetune

Vietnamese_Wav2Vec_Finetune