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---
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
|