whisper-small-korr

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3466
  • Wer: 19.9610

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: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer
0.3119 0.69 100 0.3334 20.6884
0.1223 1.39 200 0.3179 21.4336
0.0757 2.08 300 0.3234 20.3158
0.0349 2.77 400 0.3329 20.8481
0.0172 3.47 500 0.3354 20.1916
0.0059 4.16 600 0.3357 19.7480
0.0057 4.85 700 0.3396 19.9965
0.0046 5.55 800 0.3417 19.7658
0.0025 6.24 900 0.3461 20.0497
0.0029 6.93 1000 0.3466 19.9610

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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