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whisper-small-pt-cv16-fleurs

This model is a fine-tuned version of openai/whisper-small on the fsicoli/cv16-fleurs default dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2154
  • Wer: 0.1442

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-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • total_train_batch_size: 16
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5000
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.3915 0.47 1000 0.2978 0.1858
0.2942 0.93 2000 0.2500 0.1626
0.2877 1.4 3000 0.2336 0.1536
0.2303 1.87 4000 0.2225 0.1482
0.2192 2.33 5000 0.2154 0.1442

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.2.1
  • Datasets 2.16.1
  • Tokenizers 0.15.2
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Evaluation results