whisper-small-dv / README.md
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5000 epoch run
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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 - Peter Gelderbloem
    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: None
        metrics:
          - name: Wer
            type: wer
            value: 11.249434920193343

Whisper Small Dv - Peter Gelderbloem

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: 0.2863
  • Wer Ortho: 57.7129
  • Wer: 11.2494

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 Wer Ortho
0.1248 1.63 500 0.1684 12.9881 62.0447
0.0484 3.26 1000 0.1629 11.6493 58.6113
0.0315 4.89 1500 0.1878 11.7224 58.9386
0.0125 6.51 2000 0.2308 11.0895 57.2185
0.0058 8.14 2500 0.2671 11.0773 57.6224
0.0049 9.77 3000 0.2843 11.2564 57.6572
0.0033 11.4 3500 0.2845 11.0982 57.1558
0.0046 13.03 4000 0.2863 57.7129 11.2494

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 1.12.1+cu116
  • Datasets 2.4.0
  • Tokenizers 0.12.1