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metadata
language:
  - id
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_12_0
metrics:
  - wer
model-index:
  - name: Whisper small ID - Augmented
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_12_0
          type: mozilla-foundation/common_voice_12_0
          config: id
          split: test
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 5.697759963469393

Whisper small ID - Augmented

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_12_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1483
  • Wer: 5.6978

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3979 0.77 200 0.2141 9.7635
0.2625 1.54 400 0.1705 7.3636
0.1398 2.31 600 0.1551 6.9636
0.0666 3.07 800 0.1678 6.2043
0.0411 3.84 1000 0.1483 5.6978

Framework versions

  • Transformers 4.29.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.10.1
  • Tokenizers 0.13.2