whisper-small-dv / README.md
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metadata
library_name: transformers
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 - Leon Lee
    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: 9.938449768751955

Whisper Small Dv - Leon Lee

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: 0.4909
  • Wer Ortho: 53.6249
  • Wer: 9.9384

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-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.0162 6.4935 500 0.2193 57.3020 11.4285
0.0027 12.9870 1000 0.2799 55.4287 10.4983
0.0013 19.4805 1500 0.3227 55.2824 10.5105
0.0007 25.9740 2000 0.3129 54.6069 10.4149
0.0 32.4675 2500 0.3903 53.6249 9.9680
0.0 38.9610 3000 0.4478 53.6945 9.9332
0.0 45.4545 3500 0.4796 53.6458 9.9524
0.0 51.9481 4000 0.4909 53.6249 9.9384

Framework versions

  • Transformers 4.48.1
  • Pytorch 2.6.0+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0