Whisper Fine tuned Small

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

  • Loss: 0.1965
  • Wer: 11.2724

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2
  • training_steps: 102
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1398 0.4 20 0.2211 13.1623
0.0941 0.8 40 0.2144 11.8124
0.048 1.2 60 0.1997 11.2386
0.0481 1.6 80 0.1979 11.3736
0.0337 2.0 100 0.1965 11.2724

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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