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Whisper Large Catalan

This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common_voice_13_0 ca dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1458
  • Wer: 5.0700

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: 32
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 20000

Training results

Training Loss Epoch Step Validation Loss Wer
0.1059 1.02 1000 0.1744 7.6342
0.0159 3.02 2000 0.1943 7.3850
0.0526 5.02 3000 0.1899 6.8522
0.058 7.02 4000 0.1782 6.7802
0.0161 9.02 5000 0.1995 6.6339
0.065 11.02 6000 0.1563 6.4544
0.082 13.02 7000 0.1789 6.0309
0.0339 15.02 8000 0.1509 5.7554
0.0581 17.01 9000 0.1573 6.0446
0.0181 19.01 10000 0.1838 5.5913
0.0188 21.01 11000 0.1610 5.4804
0.0134 23.01 12000 0.1821 5.3953
0.008 25.01 13000 0.1748 5.3804
0.0071 27.01 14000 0.1858 5.4701
0.0371 29.01 15000 0.1610 5.6599
0.0076 31.01 16000 0.1571 5.1655
0.0181 33.01 17000 0.1449 5.4558
0.0522 35.0 18000 0.1340 5.8388
0.0356 37.0 19000 0.1458 5.0700
0.0132 39.0 20000 0.1310 5.1941

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train zuazo/whisper-large-ca

Evaluation results