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Whisper Large Arabic

This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common_voice_11_0 ar dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3231
  • Wer: 49.4320

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: 2
  • 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: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2472 0.1 1000 0.3719 58.9560
0.2015 0.2 2000 0.3487 53.5213
0.1418 1.04 3000 0.3231 49.4320
0.0921 1.14 4000 0.3284 56.1107
0.0923 1.24 5000 0.3304 61.4227
0.0483 2.08 6000 0.3460 55.952
0.0391 2.18 7000 0.3538 51.1067
0.0228 3.02 8000 0.3493 51.82
0.0206 3.12 9000 0.3729 52.4000
0.018 3.22 10000 0.3676 51.296

Framework versions

  • Transformers 4.28.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.11.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train lorenzoncina/whisper-large-ar

Evaluation results