---
tags:
- generated_from_trainer
base_model: batoula187/wav2vec2-large-xls-r-300m-arabic-colab
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-arabic-colab
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ar
      split: test[:10%]
      args: ar
    metrics:
    - type: wer
      value: 0.627304825421734
      name: Wer
---

<!-- 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 [batoula187/wav2vec2-large-xls-r-300m-arabic-colab](https://huggingface.co/batoula187/wav2vec2-large-xls-r-300m-arabic-colab) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5330
- Wer: 0.6273

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0457        | 1.6901  | 200  | 1.5030          | 0.6377 |
| 0.0408        | 3.3803  | 400  | 1.4683          | 0.6503 |
| 0.0693        | 5.0704  | 600  | 1.6023          | 0.6897 |
| 0.0766        | 6.7606  | 800  | 1.3947          | 0.6709 |
| 0.0653        | 8.4507  | 1000 | 1.5052          | 0.6858 |
| 0.0542        | 10.1408 | 1200 | 1.6550          | 0.6999 |
| 0.0535        | 11.8310 | 1400 | 1.4820          | 0.6591 |
| 0.0645        | 13.5211 | 1600 | 1.5134          | 0.6732 |
| 0.0583        | 15.2113 | 1800 | 1.4606          | 0.6561 |
| 0.0551        | 16.9014 | 2000 | 1.4476          | 0.6534 |
| 0.0462        | 18.5915 | 2200 | 1.5556          | 0.6557 |
| 0.0447        | 20.2817 | 2400 | 1.5289          | 0.6503 |
| 0.0395        | 21.9718 | 2600 | 1.5145          | 0.6434 |
| 0.0327        | 23.6620 | 2800 | 1.5916          | 0.6475 |
| 0.0317        | 25.3521 | 3000 | 1.5830          | 0.6526 |
| 0.0276        | 27.0423 | 3200 | 1.5935          | 0.6432 |
| 0.026         | 28.7324 | 3400 | 1.5330          | 0.6273 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1