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whisper-tiny

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: 0.5913
  • Wer Ortho: 0.2340
  • Wer: 0.2243

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
1.7357 2.0 50 0.7179 0.2947 0.2412
0.2772 4.0 100 0.4758 0.2404 0.2113
0.081 6.0 150 0.5069 0.2628 0.2282
0.02 8.0 200 0.5289 0.2564 0.2297
0.0044 10.0 250 0.5366 0.2452 0.2251
0.0018 12.0 300 0.5565 0.2404 0.2251
0.0011 14.0 350 0.5668 0.2388 0.2259
0.0009 16.0 400 0.5762 0.2364 0.2251
0.0007 18.0 450 0.5847 0.2348 0.2243
0.0006 20.0 500 0.5913 0.2340 0.2243

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Dataset used to train nomad-ai/whisper-tiny

Evaluation results