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Fine_tune_whisper_small

This model is a fine-tuned version of openai/whisper-small on our own recorded dataset (700 audio samples). It achieves the following results on the evaluation set:

  • Loss: 0.8225
  • Wer: 43.7477

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: 200
  • training_steps: 900
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2991 3.92 200 0.6605 44.1903
0.0185 7.84 400 0.7377 42.8624
0.0026 11.76 600 0.8087 43.0837
0.0011 15.69 800 0.8225 43.7477

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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