480min_wav2vec_xls-r53_FT
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-arabic on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7631
- Wer: 0.5522
- Cer: 0.1752
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| 1.7166 | 1.5253 | 100 | 0.2935 | 1.0749 | 0.8271 |
| 1.1245 | 3.0505 | 200 | 0.2443 | 0.9033 | 0.7330 |
| 0.9648 | 4.6015 | 300 | 0.8433 | 0.6700 | 0.2202 |
| 0.8567 | 6.1268 | 400 | 0.7753 | 0.6359 | 0.2062 |
| 0.769 | 7.6520 | 500 | 0.7855 | 0.6054 | 0.1952 |
| 0.7087 | 9.1773 | 600 | 0.7694 | 0.5903 | 0.1898 |
| 0.6554 | 10.7026 | 700 | 0.7280 | 0.5789 | 0.1856 |
| 0.6226 | 12.2278 | 800 | 0.7751 | 0.5685 | 0.1830 |
| 0.5922 | 13.7531 | 900 | 0.7454 | 0.5607 | 0.1794 |
| 0.5657 | 15.2784 | 1000 | 0.7614 | 0.5639 | 0.1788 |
| 0.5537 | 16.8036 | 1100 | 0.7438 | 0.5585 | 0.1778 |
| 0.5383 | 18.3289 | 1200 | 0.7551 | 0.5555 | 0.1762 |
| 0.5255 | 19.8541 | 1300 | 0.7631 | 0.5522 | 0.1752 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.19.1