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whisper-tiny-en

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: 0.8008
  • Wer Ortho: 0.3523
  • Wer: 0.3253

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • 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
1.593 1.79 50 1.0054 0.5003 0.4185
0.3982 3.57 100 0.7250 0.4121 0.3554
0.2075 5.36 150 0.6898 0.4226 0.3518
0.0957 7.14 200 0.6909 0.4028 0.3371
0.0412 8.93 250 0.7296 0.3695 0.3300
0.0186 10.71 300 0.7522 0.3627 0.3270
0.008 12.5 350 0.7703 0.3584 0.3288
0.0049 14.29 400 0.7756 0.3553 0.3294
0.0032 16.07 450 0.7889 0.3516 0.3235
0.0023 17.86 500 0.8008 0.3523 0.3253

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train KoRiF/whisper-tiny-en

Evaluation results