learning_rate: 5e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
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: 500
num_epochs: 5
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer
0.4772	0.4336	2000	0.3677	0.3733
0.3599	0.8671	4000	0.3126	0.3000
0.2908	1.3007	6000	0.2661	0.2659
0.2594	1.7342	8000	0.2433	0.2441
0.2041	2.1678	10000	0.2290	0.2279
0.1933	2.6013	12000	0.2107	0.2146
0.1676	3.0349	14000	0.2096	0.2117
0.1463	3.4685	16000	0.1956	0.1981
0.1332	3.9020	18000	0.1772	0.1848
0.106	4.3356	20000	0.1816	0.1788
0.1014	4.7691	22000	0.1759	0.1737

cdactvm/w2v-bert-bengali-model

w2v-bert-bengali-model