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whisper-small-tr

Automatic Speech Recognition
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metadata
language:
  - tr
license: apache-2.0
tags:
  - whisper
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Turkish
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 tr
          type: mozilla-foundation/common_voice_11_0
          config: tr
          split: test
          args: tr
        metrics:
          - name: Wer
            type: wer
            value: 17.275280898876407

Whisper Small Turkish

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

  • Loss: 0.2799
  • Wer: 17.2753
  • Cer: 4.5335

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 Cer
0.1044 1.07 1000 0.2777 18.4046 4.8810
0.0469 3.02 2000 0.2799 17.2753 4.5335
0.014 4.09 3000 0.3202 18.0800 4.9039
0.0039 6.04 4000 0.3326 18.2964 5.0192
0.0022 7.11 5000 0.3453 18.0307 4.9470

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2