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Whisper Base Bengali

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
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Dataset used to train arun100/whisper-base-bn-6

Evaluation results