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breeze-listen-dsw-small-ml

This model is a fine-tuned version of openai/whisper-small on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3647
  • Wer: 34.3837

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
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4577 1.02 100 0.4824 58.3874
0.1781 2.04 200 0.3066 41.0658
0.0935 3.06 300 0.2903 35.6441
0.057 5.0 400 0.3289 36.6172
0.0285 6.03 500 0.3425 35.3197
0.0203 7.05 600 0.3647 34.3837

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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Model size
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FP16
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Finetuned from

Collection including simpragma/breeze-listen-dsw-small-ml

Evaluation results