whisper-small-bn-3 / README.md
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metadata
language:
  - bn
license: apache-2.0
base_model: arun100/whisper-base-hi-1
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_0
metrics:
  - wer
model-index:
  - name: Whisper Base Bengali
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_16_0 bn
          type: mozilla-foundation/common_voice_16_0
          config: bn
          split: test
          args: bn
        metrics:
          - name: Wer
            type: wer
            value: 36.204844612672595

Whisper Base Bengali

This model is a fine-tuned version of arun100/whisper-base-hi-1 on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2754
  • Wer: 36.2048

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: 1e-06
  • 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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.693 1.04 500 0.6937 69.6782
0.3979 3.03 1000 0.4168 48.0703
0.3429 5.01 1500 0.3527 42.8105
0.2907 6.05 2000 0.3225 40.4267
0.2761 8.03 2500 0.3039 38.8974
0.2637 10.02 3000 0.2921 37.7927
0.2507 12.0 3500 0.2846 37.0733
0.2397 13.04 4000 0.2793 36.6004
0.243 15.03 4500 0.2763 36.3503
0.2501 17.01 5000 0.2754 36.2048

Framework versions

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