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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-Arabic-colab
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-Arabic-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0021
- Wer: 0.0191
- Cer: 0.0072
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 17.5531 | 1.0 | 51 | 5.2205 | 1.0 | 1.0 |
| 3.9441 | 2.0 | 102 | 3.1378 | 1.0 | 1.0 |
| 3.1686 | 3.0 | 153 | 3.1191 | 1.0 | 1.0 |
| 3.1558 | 4.0 | 204 | 3.1101 | 1.0 | 1.0 |
| 3.1286 | 5.0 | 255 | 3.0171 | 1.0 | 1.0 |
| 3.0755 | 6.0 | 306 | 2.9542 | 1.0 | 1.0 |
| 2.9533 | 7.0 | 357 | 2.8221 | 1.0 | 1.0 |
| 2.5924 | 8.0 | 408 | 2.1453 | 1.0 | 0.9771 |
| 1.8657 | 9.0 | 459 | 1.1540 | 0.9094 | 0.7057 |
| 0.9519 | 10.0 | 510 | 0.4219 | 0.6767 | 0.2782 |
| 0.4752 | 11.0 | 561 | 0.1646 | 0.3416 | 0.0870 |
| 0.2402 | 12.0 | 612 | 0.0551 | 0.0899 | 0.0255 |
| 0.1512 | 13.0 | 663 | 0.0307 | 0.0586 | 0.0167 |
| 0.0906 | 14.0 | 714 | 0.0172 | 0.0541 | 0.0161 |
| 0.0711 | 15.0 | 765 | 0.0141 | 0.0444 | 0.0125 |
| 0.0561 | 16.0 | 816 | 0.0114 | 0.0269 | 0.0065 |
| 0.048 | 17.0 | 867 | 0.0090 | 0.0338 | 0.0110 |
| 0.0452 | 18.0 | 918 | 0.0072 | 0.0235 | 0.0080 |
| 0.0349 | 19.0 | 969 | 0.0073 | 0.0207 | 0.0062 |
| 0.0333 | 20.0 | 1020 | 0.0054 | 0.0183 | 0.0055 |
| 0.0275 | 21.0 | 1071 | 0.0050 | 0.0280 | 0.0087 |
| 0.0262 | 22.0 | 1122 | 0.0039 | 0.0251 | 0.0088 |
| 0.0241 | 23.0 | 1173 | 0.0039 | 0.0302 | 0.0110 |
| 0.0216 | 24.0 | 1224 | 0.0035 | 0.0243 | 0.0086 |
| 0.019 | 25.0 | 1275 | 0.0033 | 0.0250 | 0.0091 |
| 0.0178 | 26.0 | 1326 | 0.0027 | 0.0238 | 0.0089 |
| 0.0169 | 27.0 | 1377 | 0.0025 | 0.0220 | 0.0080 |
| 0.0168 | 28.0 | 1428 | 0.0024 | 0.0175 | 0.0060 |
| 0.015 | 29.0 | 1479 | 0.0021 | 0.0194 | 0.0071 |
| 0.0131 | 30.0 | 1530 | 0.0021 | 0.0191 | 0.0072 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
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