whisper-medium-toi / README.md
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metadata
language:
  - toi
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - zambezi_voice/tonga
metrics:
  - wer
model-index:
  - name: Whisper Medium - Claytone Aikasote
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: tonga
          type: zambezi_voice/tonga
          config: null
          split: None
          args: 'config: toi, split: dev'
        metrics:
          - name: Wer
            type: wer
            value: 59.61628451099672

Whisper Medium - Claytone Aikasote

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

  • Loss: 2.8215
  • Wer: 59.6163

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: 4
  • eval_batch_size: 4
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4727 1.47 500 2.0656 70.8002
0.2033 2.95 1000 2.0971 67.6416
0.0658 4.42 1500 2.3894 62.0262
0.0281 5.9 2000 2.5443 62.2134
0.0104 7.37 2500 2.6873 61.8390
0.0046 8.85 3000 2.7252 60.6458
0.0004 10.32 3500 2.7891 60.8563
0.0003 11.8 4000 2.8215 59.6163

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2