Whisper Tiny (Finetuned on French)

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7793
  • Model Preparation Time: 0.0027
  • Wer: 0.4218
  • Cer: 0.1940

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • training_steps: 12000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Model Preparation Time Wer Cer
0.516 0.0833 1000 0.9995 0.0027 0.4487 0.2213
0.5283 0.1667 2000 0.9679 0.0027 0.4511 0.2207
0.5421 0.25 3000 0.9532 0.0027 0.4462 0.2172
0.5735 0.3333 4000 0.9474 0.0027 0.4365 0.2110
0.5774 0.4167 5000 0.9119 0.0027 0.4794 0.2390
0.591 0.5 6000 0.8834 0.0027 0.4171 0.2024
0.5218 0.5833 7000 0.8777 0.0027 0.4293 0.2096
0.4328 0.6667 8000 0.8750 0.0027 0.4139 0.2017
0.5392 0.75 9000 0.8736 0.0027 0.5618 0.3050
0.4311 0.8333 10000 0.8587 0.0027 0.5618 0.3030
0.4728 0.9167 11000 0.8514 0.0027 0.4293 0.2034
0.4521 1.0 12000 0.8516 0.0027 0.4220 0.2054

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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