---
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: 0.0001
- Wer: 0.0813
- Cer: 0.0362

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0166        | 1.0   | 51   | 0.0020          | 0.0944 | 0.0431 |
| 0.015         | 2.0   | 102  | 0.0018          | 0.0939 | 0.0434 |
| 0.0223        | 3.0   | 153  | 0.0034          | 0.0705 | 0.0311 |
| 0.0351        | 4.0   | 204  | 0.0089          | 0.1050 | 0.0414 |
| 0.0473        | 5.0   | 255  | 0.0051          | 0.1224 | 0.0614 |
| 0.0406        | 6.0   | 306  | 0.0084          | 0.1185 | 0.0547 |
| 0.0412        | 7.0   | 357  | 0.0030          | 0.0640 | 0.0254 |
| 0.0301        | 8.0   | 408  | 0.0157          | 0.0708 | 0.0219 |
| 0.0295        | 9.0   | 459  | 0.0027          | 0.0716 | 0.0298 |
| 0.0239        | 10.0  | 510  | 0.0077          | 0.0868 | 0.0354 |
| 0.0266        | 11.0  | 561  | 0.0017          | 0.0733 | 0.0301 |
| 0.0154        | 12.0  | 612  | 0.0015          | 0.0961 | 0.0385 |
| 0.0187        | 13.0  | 663  | 0.0006          | 0.1100 | 0.0465 |
| 0.0156        | 14.0  | 714  | 0.0015          | 0.1030 | 0.0426 |
| 0.013         | 15.0  | 765  | 0.0014          | 0.1068 | 0.0451 |
| 0.0136        | 16.0  | 816  | 0.0013          | 0.1066 | 0.0434 |
| 0.0123        | 17.0  | 867  | 0.0008          | 0.1240 | 0.0587 |
| 0.0098        | 18.0  | 918  | 0.0006          | 0.1140 | 0.0570 |
| 0.0108        | 19.0  | 969  | 0.0005          | 0.0843 | 0.0364 |
| 0.009         | 20.0  | 1020 | 0.0002          | 0.0954 | 0.0438 |
| 0.0083        | 21.0  | 1071 | 0.0003          | 0.0828 | 0.0377 |
| 0.0085        | 22.0  | 1122 | 0.0002          | 0.0648 | 0.0267 |
| 0.0073        | 23.0  | 1173 | 0.0003          | 0.0843 | 0.0373 |
| 0.0057        | 24.0  | 1224 | 0.0003          | 0.0822 | 0.0367 |
| 0.0039        | 25.0  | 1275 | 0.0002          | 0.0733 | 0.0329 |
| 0.0045        | 26.0  | 1326 | 0.0005          | 0.0754 | 0.0335 |
| 0.008         | 27.0  | 1377 | 0.0008          | 0.0803 | 0.0361 |
| 0.0045        | 28.0  | 1428 | 0.0001          | 0.0772 | 0.0340 |
| 0.0043        | 29.0  | 1479 | 0.0001          | 0.0808 | 0.0359 |
| 0.0042        | 30.0  | 1530 | 0.0001          | 0.0813 | 0.0362 |


### Framework versions

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