wav2vec2-large-xls-r-300m-Arabic
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0028
- Wer: 0.0691
- Cer: 0.0318
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- 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: 250
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
17.5167 | 1.0 | 51 | 4.8815 | 1.0 | 1.0 |
4.0416 | 2.0 | 102 | 3.1278 | 1.0 | 1.0 |
3.1594 | 3.0 | 153 | 3.1154 | 1.0 | 1.0 |
3.1534 | 4.0 | 204 | 3.0524 | 1.0 | 1.0 |
3.0361 | 5.0 | 255 | 2.8827 | 1.0 | 1.0 |
2.799 | 6.0 | 306 | 2.4063 | 1.0 | 0.9571 |
1.9731 | 7.0 | 357 | 1.0794 | 0.9762 | 0.5933 |
0.7265 | 8.0 | 408 | 0.2350 | 0.4686 | 0.1378 |
0.2788 | 9.0 | 459 | 0.0527 | 0.1055 | 0.0265 |
0.1396 | 10.0 | 510 | 0.0263 | 0.1063 | 0.0386 |
0.0891 | 11.0 | 561 | 0.0245 | 0.0829 | 0.0247 |
0.0667 | 12.0 | 612 | 0.0119 | 0.0368 | 0.0091 |
0.0594 | 13.0 | 663 | 0.0154 | 0.0405 | 0.0113 |
0.0467 | 14.0 | 714 | 0.0109 | 0.0509 | 0.0203 |
0.0354 | 15.0 | 765 | 0.0129 | 0.0818 | 0.0320 |
0.0332 | 16.0 | 816 | 0.0086 | 0.0933 | 0.0486 |
0.0283 | 17.0 | 867 | 0.0135 | 0.0970 | 0.0431 |
0.0244 | 18.0 | 918 | 0.0083 | 0.0650 | 0.0276 |
0.0268 | 19.0 | 969 | 0.0071 | 0.0286 | 0.0101 |
0.0245 | 20.0 | 1020 | 0.0058 | 0.0320 | 0.0120 |
0.0206 | 21.0 | 1071 | 0.0031 | 0.1059 | 0.0455 |
0.0162 | 22.0 | 1122 | 0.0050 | 0.0699 | 0.0292 |
0.0152 | 23.0 | 1173 | 0.0054 | 0.0517 | 0.0192 |
0.014 | 24.0 | 1224 | 0.0037 | 0.0654 | 0.0266 |
0.0161 | 25.0 | 1275 | 0.0024 | 0.0320 | 0.0127 |
0.0156 | 26.0 | 1326 | 0.0027 | 0.0565 | 0.0244 |
0.0122 | 27.0 | 1377 | 0.0036 | 0.0587 | 0.0260 |
0.0105 | 28.0 | 1428 | 0.0026 | 0.0494 | 0.0216 |
0.0114 | 29.0 | 1479 | 0.0028 | 0.0613 | 0.0283 |
0.0087 | 30.0 | 1530 | 0.0028 | 0.0691 | 0.0318 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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