Whisper openai-whisper-small

This model is a fine-tuned version of openai/whisper-small on the llamadas ecu911 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2243
  • Wer: 48.5283

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: 2
  • eval_batch_size: 1
  • 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: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.6421 2.6596 500 0.9066 53.5438
0.1036 5.3191 1000 1.0305 50.4841
0.0184 7.9787 1500 1.1467 48.7413
0.0046 10.6383 2000 1.2243 48.5283

Framework versions

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