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Whisper Small ES-CL - Roberto Castro-Vexler

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

  • Loss: 0.1552
  • Wer: 5.9310

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: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0038 8.6207 1000 0.1381 6.1975
0.0002 17.2414 2000 0.1466 5.8510
0.0001 25.8621 3000 0.1528 5.9709
0.0001 34.4828 4000 0.1552 5.9310

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.1
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Dataset used to train rcastrovexler/whisper-small-es-cl

Evaluation results