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Whisper Large Galician

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

  • Loss: 0.3605
  • Wer: 6.9398

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
0.0126 4.01 1000 0.2128 8.3558
0.0032 9.01 2000 0.2262 6.9416
0.0022 14.01 3000 0.2528 7.1123
0.0025 19.01 4000 0.2643 7.3641
0.0015 24.01 5000 0.2596 7.3365
0.0014 29.01 6000 0.2723 7.6366
0.0008 34.01 7000 0.2778 7.6090
0.0003 39.01 8000 0.2880 7.2261
0.0004 44.01 9000 0.2920 7.6745
0.0001 49.01 10000 0.2854 7.4089
0.0 54.01 11000 0.3027 7.4365
0.0 59.01 12000 0.3159 7.4055
0.0 64.01 13000 0.3242 7.3693
0.0 69.01 14000 0.3312 7.3072
0.0 74.01 15000 0.3379 7.0226
0.0 79.01 16000 0.3442 7.0019
0.0 84.01 17000 0.3500 6.9933
0.0 89.01 18000 0.3550 6.9605
0.0 94.01 19000 0.3589 6.9467
0.0 99.01 20000 0.3605 6.9398

Framework versions

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