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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: 3.0846
  • Wer: 109.9932

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-07
  • 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
1.6852 3.8760 500 3.5237 148.8184
1.2494 7.7519 1000 3.2200 121.6070
1.2202 11.6279 1500 3.1493 125.3883
1.0905 15.5039 2000 3.1099 113.9095
1.0606 19.3798 2500 3.0905 110.1958
1.0858 23.2558 3000 3.0846 109.9932

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_test1.10

Evaluation results