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abbenedekwhisper-base.en-finetuning2-D3K

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

  • Loss: 4.7781
  • Cer: 64.7190
  • Wer: 119.5364
  • Ser: 100.0
  • Cer Clean: 3.5058
  • Wer Clean: 6.2914
  • Ser Clean: 7.0175

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: 5e-08
  • train_batch_size: 16
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Wer Ser Cer Clean Wer Clean Ser Clean
7.5369 0.53 100 6.7220 63.7730 128.1457 100.0 4.1180 6.9536 8.7719
7.0363 1.06 200 6.1829 65.0529 123.8411 100.0 3.2832 5.6291 7.0175
6.417 1.6 300 5.7959 64.1625 121.1921 100.0 3.2832 5.6291 7.0175
6.0146 2.13 400 5.4587 64.7746 121.8543 100.0 3.6728 6.6225 7.8947
5.6687 2.66 500 5.2287 65.3311 120.5298 100.0 3.7284 6.6225 7.8947
5.3902 3.19 600 5.0691 65.1085 121.1921 100.0 3.5615 6.2914 7.0175
5.2512 3.72 700 4.9358 64.7190 120.1987 100.0 3.2832 5.9603 6.1404
5.1258 4.26 800 4.8451 64.7190 119.5364 100.0 3.5058 6.2914 7.0175
5.0472 4.79 900 4.7950 64.7190 119.5364 100.0 3.5058 6.2914 7.0175
4.9871 5.32 1000 4.7781 64.7190 119.5364 100.0 3.5058 6.2914 7.0175

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.14.5
  • Tokenizers 0.15.2
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