This model is a fine-tuned version of arun100/whisper-base-bn-3 on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set:

Loss: 0.2078
Wer: 28.8185

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-07
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1568	1.72	500	0.2145	29.8350
0.1507	3.43	1000	0.2132	29.5594
0.1466	5.15	1500	0.2119	29.3576
0.1463	6.86	2000	0.2106	29.2927
0.1426	8.58	2500	0.2098	29.2220
0.139	10.29	3000	0.2093	29.1075
0.1373	12.01	3500	0.2087	29.0878
0.1362	13.72	4000	0.2084	28.9769
0.1333	15.44	4500	0.2081	28.9129
0.1332	17.15	5000	0.2079	28.8945
0.1363	18.87	5500	0.2078	28.8185

Framework versions

Transformers 4.37.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.16.2.dev0
Tokenizers 0.15.0

arun100/whisper-base-bn-6

Whisper Base Bengali

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

arun100/
whisper-base-bn-6