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metadata
library_name: transformers
language:
  - id
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Tiny - FineTuned - Id -
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: id
          split: None
          args: 'config: id, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 59.896729776247845

Whisper Tiny - FineTuned - Id -

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4286
  • Wer: 59.8967

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use 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: 2
  • training_steps: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.7163 0.0159 1 1.8245 86.1446
1.7097 0.0317 2 1.8245 86.1446
1.7377 0.0476 3 1.8245 86.1446
1.65 0.0635 4 1.8245 86.1446
1.9103 0.0794 5 1.7649 68.5026
1.7345 0.0952 6 1.6261 74.1824
1.5202 0.1111 7 1.5249 59.6386
1.5166 0.1270 8 1.4786 59.3804
1.5636 0.1429 9 1.4523 59.5525
1.5493 0.1587 10 1.4286 59.8967

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3