---
tags:
- generated_from_trainer
base_model: batoula187/wav2vec2-large-xls-r-300m-arabic-colab
datasets:
- common_voice_12_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_12_0
      type: common_voice_12_0
      config: ar
      split: test[:10%]
      args: ar
    metrics:
    - type: wer
      value: 0.7661710754972002
      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_12_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0728
- Wer: 0.7662

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.1061        | 2.2599  | 200  | 1.8297          | 0.8034 |
| 0.1496        | 4.5198  | 400  | 1.6173          | 0.7955 |
| 0.2105        | 6.7797  | 600  | 1.6220          | 0.8040 |
| 0.1798        | 9.0395  | 800  | 2.2087          | 0.8405 |
| 0.1389        | 11.2994 | 1000 | 1.7900          | 0.7868 |
| 0.1143        | 13.5593 | 1200 | 1.7566          | 0.7886 |
| 0.103         | 15.8192 | 1400 | 1.8148          | 0.7689 |
| 0.0904        | 18.0791 | 1600 | 1.8059          | 0.7627 |
| 0.0766        | 20.3390 | 1800 | 2.1398          | 0.7907 |
| 0.0682        | 22.5989 | 2000 | 2.0384          | 0.7779 |
| 0.0583        | 24.8588 | 2200 | 2.0727          | 0.7658 |
| 0.0575        | 27.1186 | 2400 | 2.1649          | 0.7758 |
| 0.0582        | 29.3785 | 2600 | 2.0728          | 0.7662 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1