whisper-small-dv / README.md
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metadata
language:
  - dv
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Small Dv - Sanchit Gandhi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 13
          type: mozilla-foundation/common_voice_13_0
          config: dv
          split: test
          args: dv
        metrics:
          - name: Wer
            type: wer
            value: 11.631950481621868

Whisper Small Dv - Sanchit Gandhi

This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3085
  • Wer Ortho: 58.3606
  • Wer: 11.6320

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-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 4000

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.1119 1.63 500 0.1645 60.8817 12.9082
0.0457 3.26 1000 0.1677 59.3286 11.7450
0.0317 4.89 1500 0.1903 58.3258 11.3798
0.012 6.51 2000 0.2292 58.0403 11.7085
0.007 8.14 2500 0.2595 56.9538 11.0982
0.0061 9.77 3000 0.2606 56.6404 10.8878
0.0052 11.4 3500 0.2737 56.8911 11.1799
0.0033 13.03 4000 0.3085 58.3606 11.6320

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3