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metadata
language:
  - tr
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-medium
model-index:
  - name: Whisper Medium Turkish
    results:
      - task:
          type: automatic-speech-recognition
          name: 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:
          - type: wer
            value: 11.068934102641968
            name: Wer

Whisper Medium Turkish

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

  • Loss: 0.2780
  • Wer: 11.0689

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
0.0742 1.07 1000 0.2104 12.3975
0.0345 3.02 2000 0.2182 11.6573
0.0103 4.09 3000 0.2489 11.7921
0.0018 6.04 4000 0.2657 11.0746
0.0005 7.11 5000 0.2780 11.0689

Framework versions

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