Whisper Tunisien
This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS30s_filtred1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 4.3957
- Wer: 103.8961
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-06
- 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: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.4403 | 16.9492 | 1000 | 3.2224 | 99.5671 |
0.1001 | 33.8983 | 2000 | 3.4970 | 104.5214 |
0.0159 | 50.8475 | 3000 | 3.8371 | 102.8379 |
0.0057 | 67.7966 | 4000 | 4.0061 | 103.9442 |
0.003 | 84.7458 | 5000 | 4.1216 | 104.8581 |
0.0018 | 101.6949 | 6000 | 4.2086 | 104.4733 |
0.0012 | 118.6441 | 7000 | 4.2855 | 104.9543 |
0.0009 | 135.5932 | 8000 | 4.3365 | 103.6556 |
0.0007 | 152.5424 | 9000 | 4.3818 | 103.9442 |
0.0006 | 169.4915 | 10000 | 4.3957 | 103.8961 |
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_test1.8
Evaluation results
- Wer on Tunisian_dataset_STT-TTS30s_filtred1.0self-reported103.896