whisper-tiny-minds14-en-us

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6155
  • Wer: 0.3211
  • Wer Ortho: 0.3263

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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Wer Ortho
0.2739 3.4483 100 0.4633 0.3400 0.3523
0.0319 6.8966 200 0.5263 0.3294 0.3405
0.0039 10.3448 300 0.6010 0.3288 0.3350
0.0012 13.7931 400 0.6155 0.3211 0.3263
0.0009 17.2414 500 0.6408 0.3235 0.3282

Framework versions

  • Transformers 4.57.6
  • Pytorch 2.8.0+cu128
  • Datasets 4.8.4
  • Tokenizers 0.22.2
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