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Whisper Large-V2 Galician

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_13_0 gl dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3601
  • Wer: 5.9879

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
0.0185 4.01 1000 0.1896 6.3569
0.0067 9.01 2000 0.2083 6.3862
0.0038 14.01 3000 0.2291 6.4621
0.0022 19.01 4000 0.2412 6.4794
0.0013 24.01 5000 0.2515 6.4673
0.0023 29.01 6000 0.2570 6.6432
0.0018 34.01 7000 0.2474 6.6380
0.0017 39.01 8000 0.2530 6.9312
0.0001 44.01 9000 0.2758 6.2379
0.0001 49.01 10000 0.2952 6.1241
0.0001 54.01 11000 0.3056 6.0499
0.0 59.01 12000 0.3152 5.9948
0.0 64.01 13000 0.3244 6.0310
0.0 69.01 14000 0.3336 6.0586
0.0 74.01 15000 0.3428 6.0344
0.0 79.01 16000 0.3518 6.0017
0.0 84.01 17000 0.3601 5.9879
0.0 89.01 18000 0.3675 6.0103
0.0 94.01 19000 0.3729 6.0068
0.0 99.01 20000 0.3753 6.0172

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-v2-gl

Evaluation results