whisper-small-vi-2 / README.md
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metadata
language:
  - vi
license: apache-2.0
base_model: openai/whisper-small
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_0
metrics:
  - wer
model-index:
  - name: Whisper Small Vienamese
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_16_0 vi
          type: mozilla-foundation/common_voice_16_0
          config: vi
          split: test
          args: vi
        metrics:
          - name: Wer
            type: wer
            value: 24.56800162634682

Whisper Small Vienamese

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_16_0 vi dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6705
  • Wer: 24.5680

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-06
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 2500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0174 33.0 500 0.6207 24.6696
0.0045 66.0 1000 0.6705 24.5680
0.0027 99.01 1500 0.6945 25.2795
0.002 133.0 2000 0.7079 26.4790
0.0018 166.0 2500 0.7127 26.3976

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0