whisper-base-en-emo-v1

This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0(Emotional Tag) dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9660
  • Wer: 120.1005

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: 4
  • 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
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0074 40.0 1000 0.8128 130.1508
0.0002 80.0 2000 0.9065 114.5729
0.0001 120.0 3000 0.9507 109.0452
0.0001 160.0 4000 0.9660 120.1005

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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Dataset used to train iFaz/whisper-base-en-emo-v1

Evaluation results