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Librarian Bot: Add base_model information to model (#1)
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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-small
model-index:
  - name: Whisper Small 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: 18.55567623290319
            name: Wer

Whisper Small Czech CV11

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

  • Loss: 0.3587
  • Wer: 18.5557

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: 64
  • eval_batch_size: 32
  • 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
0.0392 4.01 1000 0.2857 19.6675
0.0028 8.02 2000 0.3204 18.3495
0.0011 12.03 3000 0.3402 18.5336
0.0008 16.04 4000 0.3537 18.4563
0.0007 21.01 5000 0.3587 18.5557

Framework versions

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