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JacobLinCool/wft-test-model-merged

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.038M params151 MBsafetensors✓ 1 checksumupdated today
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wft-test-model

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

  • Loss: 0.1248
  • Wer: 4.7244
  • Cer: 92.6847
  • Decode Time: 0.5481
  • Wer Time: 0.0069
  • Cer Time: 0.0040

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: 0.0005
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 100

Training results

Training Loss Epoch Step Validation Loss Wer Cer Decode Time Wer Time Cer Time
2.4107 0.1 10 1.9892 303.5433 117.1875 0.5449 0.0307 0.0039
1.2109 1.01 20 1.1659 155.1181 91.2642 0.5278 0.0062 0.0036
0.8855 1.11 30 0.8104 30.7087 56.8182 0.4832 0.0069 0.0041
0.4367 2.02 40 0.6315 25.1969 74.5739 0.5295 0.0058 0.0034
0.4398 2.12 50 0.4566 17.3228 91.9744 0.6078 0.0055 0.0030
0.2291 3.03 60 0.3006 9.0551 100.7102 0.5659 0.0058 0.0031
0.2281 3.13 70 0.2144 7.4803 90.4830 0.5507 0.0046 0.0030
0.111 4.04 80 0.1736 5.9055 89.3466 0.6595 0.0063 0.0032
0.0695 4.14 90 0.1345 4.7244 87.9261 0.6369 0.0402 0.0182
0.0761 5.05 100 0.1248 4.7244 92.6847 0.5481 0.0069 0.0040

Framework versions

  • PEFT 0.13.2
  • Transformers 4.45.2
  • Pytorch 2.5.0
  • Datasets 3.0.2
  • Tokenizers 0.20.1