Whisper large-v2 Test

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 16 Albanian dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7073
  • Wer: 34.0530

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.1135 4.63 500 0.6519 44.8880
0.02 9.26 1000 0.6575 39.3483
0.0075 13.89 1500 0.6073 35.6823
0.0016 18.52 2000 0.6347 34.9084
0.0008 23.15 2500 0.6484 34.9491
0.0001 27.78 3000 0.6765 34.4196
0.0001 32.41 3500 0.6897 33.9308
0.0001 37.04 4000 0.6988 34.1752
0.0001 41.67 4500 0.7048 33.9715
0.0001 46.3 5000 0.7073 34.0530

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Evaluation results