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whisper-base-bn-3

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Bengali
whisper
whisper-event
Generated from Trainer
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metadata
language:
  - bn
license: apache-2.0
base_model: arun100/whisper-base-bn
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: 29.92358146984869

Whisper Base Bengali

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

  • Loss: 0.2151
  • Wer: 29.9236

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: 8500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2476 1.72 500 0.2751 36.1695
0.2284 3.43 1000 0.2622 35.1668
0.213 5.15 1500 0.2524 34.2022
0.2048 6.86 2000 0.2447 33.5266
0.1948 8.58 2500 0.2382 32.7495
0.1852 10.29 3000 0.2334 32.2322
0.1789 12.01 3500 0.2295 31.7244
0.1738 13.72 4000 0.2260 31.2341
0.166 15.44 4500 0.2236 30.9562
0.1629 17.15 5000 0.2214 30.8171
0.1636 18.87 5500 0.2194 30.4368
0.1578 20.58 6000 0.2181 30.2520
0.1628 22.3 6500 0.2170 30.1858
0.1566 24.01 7000 0.2161 30.0694
0.1564 25.73 7500 0.2156 29.9943
0.1545 27.44 8000 0.2153 29.9294
0.1548 29.16 8500 0.2151 29.9236

Framework versions

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