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Whisper-Small-TF-TIMIT-FLEUR-Normalizado

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7395
  • Wer: 85.3796

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: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5923 1.27 500 0.9379 98.7612
0.1823 2.54 1000 0.6721 89.3262
0.0852 3.81 1500 0.6534 86.1141
0.0327 5.08 2000 0.6794 84.4019
0.0106 6.35 2500 0.7170 82.5587
0.0064 7.61 3000 0.7395 85.3796

Framework versions

  • Transformers 4.28.0.dev0
  • Pytorch 1.13.0
  • Datasets 2.1.0
  • Tokenizers 0.13.2
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