whisper-tiny-300

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

  • Loss: nan
  • Wer Ortho: 108.1081
  • Wer: 113.5135

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 30
  • training_steps: 300
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.0 20.0 60 nan 108.1081 113.5135
0.0 40.0 120 nan 108.1081 113.5135
0.0 60.0 180 nan 108.1081 113.5135
0.0 80.0 240 nan 108.1081 113.5135

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Evaluation results