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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: openai/whisper-medium
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: da
          split: test
          args: da
        metrics:
          - name: Wer
            type: wer
            value: 16.228300894266177

openai/whisper-medium

This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6569
  • Wer: 16.2283

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0229 7.01 1000 0.4464 16.5124
0.0072 15.0 2000 0.5081 16.1336
0.0048 22.01 3000 0.5193 16.6597
0.0034 30.0 4000 0.5715 16.8964
0.0005 37.01 5000 0.5998 16.4440
0.0007 45.01 6000 0.5908 16.8017
0.0001 53.0 7000 0.6093 16.2336
0.0001 60.01 8000 0.6405 16.3335
0.0 68.0 9000 0.6524 16.2493
0.0 75.01 10000 0.6569 16.2283

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2