Whisper Tiny 1000 Audios - vfranchis

This model is a fine-tuned version of openai/whisper-tiny on the 1000 audios 1.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5691
  • Wer: 30.7692

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: 25
  • training_steps: 300
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4694 0.4 25 1.0082 38.4615
0.2677 0.8 50 0.7480 46.1538
0.1034 1.2 75 0.6340 46.1538
0.0672 1.6 100 0.6319 46.1538
0.0547 2.0 125 0.5773 30.7692
0.0299 2.4 150 0.5612 30.7692
0.022 2.8 175 0.5784 30.7692
0.0218 3.2 200 0.5702 30.7692
0.0127 3.6 225 0.5721 30.7692
0.013 4.0 250 0.5554 30.7692
0.0084 4.4 275 0.5680 30.7692
0.0102 4.8 300 0.5691 30.7692

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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