whisper-small-bak / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
  - whisper-event
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: openai/whisper-small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: ba
          split: test
          args: ba
        metrics:
          - name: Wer
            type: wer
            value: 20.90095725311917

openai/whisper-small

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

  • Loss: 0.2116
  • Wer: 20.9010

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: 16
  • eval_batch_size: 8
  • 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
0.2362 0.2 1000 0.3219 35.4541
0.1566 1.04 2000 0.2583 27.1784
0.1325 1.24 3000 0.2447 24.9120
0.129 2.07 4000 0.2217 22.3117
0.1375 2.27 5000 0.2116 20.9010

Framework versions

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