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metadata
language:
  - uz
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
metrics:
  - wer
model-index:
  - name: Whisper Large v3 Turbo - Bahriddin Muminov
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16.1
          type: mozilla-foundation/common_voice_16_1
          config: uz
          split: test
          args: 'config: uz, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 28.258182136033867

Whisper Large v3 Turbo - Bahriddin Muminov

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2958
  • Wer: 28.2582

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: 1000
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.429 0.66 2000 0.4073 38.0018
0.2671 1.32 4000 0.3378 31.0778
0.2511 1.98 6000 0.3102 29.2484
0.1539 2.64 8000 0.3022 30.0763
0.111 3.3 10000 0.2958 28.2582

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2