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Whisper tiny epoch test - Perrie

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4754
  • Cer: 57.5895

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: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • 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: 700
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Cer
0.4064 0.99 700 0.4476 33.9306
0.3595 1.99 1400 0.4218 29.0735
0.2349 2.98 2100 0.4197 25.9553
0.1507 3.97 2800 0.4237 25.9104
0.1003 4.96 3500 0.4309 35.9495
0.0601 5.96 4200 0.4442 29.8821
0.0481 6.95 4900 0.4551 36.7132
0.0296 7.94 5600 0.4640 38.9224
0.0207 8.94 6300 0.4721 47.1645
0.0169 9.93 7000 0.4754 57.5895

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 1.12.1
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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