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Librarian Bot: Add base_model information to model (#2)
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metadata
language:
  - cs
license: apache-2.0
tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-medium
model-index:
  - name: Whisper Medium Czech CV11
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: cs
          split: test
        metrics:
          - type: wer
            value: 11.689339690370561
            name: Wer

Whisper Medium Czech CV11

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

  • Loss: 0.2537
  • Wer: 11.6893

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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0384 2.02 1000 0.2167 13.5467
0.0061 4.03 2000 0.2373 12.9172
0.0018 6.05 3000 0.2407 12.0409
0.0007 8.07 4000 0.2463 11.7685
0.0003 10.09 5000 0.2537 11.6893

Framework versions

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