---
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 a local dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 0.0703
- Cer: 0.0310

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.1001        | 1.0   | 51   | 0.0159          | 0.0647 | 0.0295 |
| 0.0576        | 2.0   | 102  | 0.0109          | 0.0819 | 0.0408 |
| 0.0598        | 3.0   | 153  | 0.0096          | 0.1153 | 0.0541 |
| 0.0636        | 4.0   | 204  | 0.0099          | 0.0594 | 0.0239 |
| 0.0642        | 5.0   | 255  | 0.0107          | 0.1043 | 0.0447 |
| 0.0551        | 6.0   | 306  | 0.0106          | 0.0575 | 0.0208 |
| 0.0543        | 7.0   | 357  | 0.0078          | 0.0157 | 0.0042 |
| 0.0516        | 8.0   | 408  | 0.0068          | 0.1144 | 0.0533 |
| 0.0454        | 9.0   | 459  | 0.0054          | 0.1058 | 0.0547 |
| 0.0308        | 10.0  | 510  | 0.0041          | 0.0742 | 0.0364 |
| 0.0296        | 11.0  | 561  | 0.0042          | 0.1146 | 0.0540 |
| 0.0252        | 12.0  | 612  | 0.0028          | 0.0971 | 0.0453 |
| 0.0236        | 13.0  | 663  | 0.0026          | 0.0803 | 0.0359 |
| 0.0238        | 14.0  | 714  | 0.0023          | 0.0783 | 0.0334 |
| 0.0185        | 15.0  | 765  | 0.0023          | 0.0654 | 0.0272 |
| 0.0185        | 16.0  | 816  | 0.0023          | 0.0522 | 0.0182 |
| 0.0159        | 17.0  | 867  | 0.0012          | 0.0396 | 0.0130 |
| 0.0161        | 18.0  | 918  | 0.0020          | 0.0580 | 0.0216 |
| 0.0142        | 19.0  | 969  | 0.0010          | 0.0168 | 0.0037 |
| 0.0164        | 20.0  | 1020 | 0.0009          | 0.0511 | 0.0221 |
| 0.011         | 21.0  | 1071 | 0.0006          | 0.0192 | 0.0054 |
| 0.0087        | 22.0  | 1122 | 0.0004          | 0.0198 | 0.0058 |
| 0.0083        | 23.0  | 1173 | 0.0004          | 0.0251 | 0.0093 |
| 0.0085        | 24.0  | 1224 | 0.0004          | 0.0677 | 0.0314 |
| 0.0054        | 25.0  | 1275 | 0.0003          | 0.0587 | 0.0250 |
| 0.0057        | 26.0  | 1326 | 0.0002          | 0.0435 | 0.0172 |
| 0.007         | 27.0  | 1377 | 0.0005          | 0.0696 | 0.0305 |
| 0.007         | 28.0  | 1428 | 0.0003          | 0.0673 | 0.0294 |
| 0.0059        | 29.0  | 1479 | 0.0001          | 0.0688 | 0.0301 |
| 0.0045        | 30.0  | 1530 | 0.0001          | 0.0703 | 0.0310 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2