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Whisper Tunisien

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

  • Loss: 2.1002
  • Wer: 69.0947

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
  • 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: 7000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.2207 62.5 500 2.2689 90.9469
0.8267 125.0 1000 2.0114 80.4370
0.6297 187.5 1500 1.9396 73.5692
0.5283 250.0 2000 1.9364 70.5515
0.4231 312.5 2500 1.9509 70.4475
0.3683 375.0 3000 1.9729 74.2976
0.319 437.5 3500 1.9950 73.2570
0.2884 500.0 4000 2.0182 72.6327
0.259 562.5 4500 2.0410 72.5286
0.2364 625.0 5000 2.0619 69.0947
0.2181 687.5 5500 2.0780 69.0947
0.2133 750.0 6000 2.0901 68.8866
0.201 812.5 6500 2.0979 68.8866
0.2033 875.0 7000 2.1002 69.0947

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Dataset used to train Arbi-Houssem/TunLangModel1.4

Evaluation results