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Whisper Tunisien

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

  • Loss: 4.7577
  • Wer: 117.6907

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5147 7.7519 500 3.1417 128.5618
0.0559 15.5039 1000 3.8111 132.5456
0.01 23.2558 1500 4.2115 120.1891
0.0029 31.0078 2000 4.4628 120.3916
0.0017 38.7597 2500 4.6127 111.2086
0.0011 46.5116 3000 4.6945 124.6455
0.0009 54.2636 3500 4.7426 113.3018
0.0009 62.0155 4000 4.7577 117.6907

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Finetuned from

Dataset used to train Arbi-Houssem/TunLangModel_test1.9

Evaluation results