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metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: Compare-XLS-R-to-Whisper-demo-google-colab-Ezra_William_Prod
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: id
          split: test
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 1

Compare-XLS-R-to-Whisper-demo-google-colab-Ezra_William_Prod

This model is a fine-tuned version of openai/whisper-small on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Wer: 1.0

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-06
  • 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: linear
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0 1.0 278 nan 1.0
0.0 2.0 556 nan 1.0
0.0 3.0 834 nan 1.0
0.0 4.0 1112 nan 1.0
0.0 5.0 1390 nan 1.0
0.0 6.0 1668 nan 1.0
0.0 7.0 1946 nan 1.0
0.0 8.0 2224 nan 1.0
0.0 9.0 2502 nan 1.0
0.0 10.0 2780 nan 1.0
0.0 11.0 3058 nan 1.0
0.0 12.0 3336 nan 1.0

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1