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Whisper Tunisien

This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS15s_filtred1.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 6.8348
  • Wer: 102.7009

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: 0.0005
  • 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: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.1414 3.8760 500 4.1822 181.0263
0.4667 7.7519 1000 5.0049 108.1702
0.1821 11.6279 1500 5.5927 102.7684
0.068 15.5039 2000 6.2194 106.2120
0.011 19.3798 2500 6.3815 103.0385
0.0003 23.2558 3000 6.8348 102.7009

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Dataset used to train Arbi-Houssem/TunLangModel_test1.11

Evaluation results