---
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: 0.0016
- Wer: 0.0180
- Cer: 0.0050

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 17.4389       | 1.0   | 51   | 5.2001          | 1.0    | 1.0    |
| 3.9365        | 2.0   | 102  | 3.1379          | 1.0    | 1.0    |
| 3.1693        | 3.0   | 153  | 3.1153          | 1.0    | 1.0    |
| 3.1436        | 4.0   | 204  | 3.0695          | 1.0    | 1.0    |
| 3.0914        | 5.0   | 255  | 2.9734          | 1.0    | 1.0    |
| 2.9509        | 6.0   | 306  | 2.7532          | 1.0    | 1.0    |
| 2.4865        | 7.0   | 357  | 1.8412          | 1.0    | 0.9310 |
| 1.2609        | 8.0   | 408  | 0.3920          | 0.5536 | 0.1712 |
| 0.4001        | 9.0   | 459  | 0.0803          | 0.1065 | 0.0262 |
| 0.1689        | 10.0  | 510  | 0.0340          | 0.0469 | 0.0119 |
| 0.1134        | 11.0  | 561  | 0.0240          | 0.0510 | 0.0150 |
| 0.0756        | 12.0  | 612  | 0.0140          | 0.0355 | 0.0106 |
| 0.0612        | 13.0  | 663  | 0.0098          | 0.0289 | 0.0086 |
| 0.0472        | 14.0  | 714  | 0.0087          | 0.0245 | 0.0066 |
| 0.0443        | 15.0  | 765  | 0.0075          | 0.0242 | 0.0066 |
| 0.0404        | 16.0  | 816  | 0.0072          | 0.0275 | 0.0079 |
| 0.0329        | 17.0  | 867  | 0.0056          | 0.0146 | 0.0040 |
| 0.0322        | 18.0  | 918  | 0.0058          | 0.0165 | 0.0044 |
| 0.0277        | 19.0  | 969  | 0.0056          | 0.0226 | 0.0063 |
| 0.0247        | 20.0  | 1020 | 0.0040          | 0.0180 | 0.0045 |
| 0.0234        | 21.0  | 1071 | 0.0050          | 0.0179 | 0.0052 |
| 0.0186        | 22.0  | 1122 | 0.0034          | 0.0138 | 0.0037 |
| 0.0178        | 23.0  | 1173 | 0.0032          | 0.0139 | 0.0039 |
| 0.0163        | 24.0  | 1224 | 0.0025          | 0.0158 | 0.0042 |
| 0.0165        | 25.0  | 1275 | 0.0023          | 0.0163 | 0.0043 |
| 0.0138        | 26.0  | 1326 | 0.0019          | 0.0141 | 0.0036 |
| 0.0145        | 27.0  | 1377 | 0.0019          | 0.0183 | 0.0047 |
| 0.0128        | 28.0  | 1428 | 0.0019          | 0.0178 | 0.0048 |
| 0.012         | 29.0  | 1479 | 0.0017          | 0.0177 | 0.0048 |
| 0.0121        | 30.0  | 1530 | 0.0016          | 0.0180 | 0.0050 |


### Framework versions

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