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whisper-base-bn-7

Automatic Speech Recognition
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Bengali
whisper
whisper-event
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metadata
language:
  - bn
license: apache-2.0
base_model: arun100/whisper-base-bn-6
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: 27.7209560369744

Whisper Base Bengali

This model is a fine-tuned version of arun100/whisper-base-bn-6 on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2028
  • Wer: 27.7210

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: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1388 1.72 500 0.2076 28.8529
0.1335 3.43 1000 0.2068 28.6171
0.1297 5.15 1500 0.2061 28.4462
0.13 6.86 2000 0.2050 28.4274
0.126 8.58 2500 0.2046 28.3500
0.122 10.29 3000 0.2044 28.1872
0.1205 12.01 3500 0.2039 28.1715
0.1187 13.72 4000 0.2038 28.0136
0.1152 15.44 4500 0.2035 28.0503
0.1133 17.15 5000 0.2035 28.0395
0.1167 18.87 5500 0.2031 27.9071
0.1119 20.58 6000 0.2032 27.8288
0.1168 22.3 6500 0.2030 27.8306
0.1129 24.01 7000 0.2029 27.7778
0.112 25.73 7500 0.2030 27.7415
0.1105 27.44 8000 0.2030 27.7482
0.1114 29.16 8500 0.2028 27.7608
0.1102 30.87 9000 0.2029 27.7357
0.1115 32.59 9500 0.2028 27.7210
0.1083 34.31 10000 0.2028 27.7353

Framework versions

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