vi_whisper-small / README.md
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metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: vi_whisper-small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Vivos + Commonvoice
          type: vivos
          config: None
          split: None
        metrics:
          - name: Wer
            type: wer
            value: 21.8855

vi_whisper-small

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

  • Loss: 0.2894
  • Wer: 21.8855

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

In training phase i used VIVOS dataset and cleaned CommonVoice The VIVOS evaluation dataset was used

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • 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: 8000

Training results

Training Loss Epoch Step Validation Loss Wer
0.249 1.1 1000 0.3766 32.1678
0.1416 2.2 2000 0.2881 46.4646
0.0839 3.3 3000 0.2799 22.7791
0.0546 4.41 4000 0.2894 21.8855
0.0256 5.51 5000 0.3023 32.2973
0.0111 6.61 6000 0.3061 31.0153
0.0028 7.71 7000 0.3143 27.1691
0.0014 8.81 8000 0.3187 27.3634

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3