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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