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---
license: apache-2.0
tags:
- automatic-speech-recognition
- arabic_speech_corpus
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-ar
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-xls-r-300m-ar
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ARABIC_SPEECH_CORPUS - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3212
- Wer: 0.0636
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0793 | 8.85 | 1000 | 0.1626 | 0.0786 |
| 0.0396 | 17.7 | 2000 | 0.2199 | 0.0807 |
| 0.0285 | 26.55 | 3000 | 0.2289 | 0.0694 |
| 0.021 | 35.4 | 4000 | 0.2662 | 0.0722 |
| 0.0177 | 44.25 | 5000 | 0.2459 | 0.0744 |
| 0.0155 | 53.1 | 6000 | 0.2689 | 0.0679 |
| 0.0149 | 61.95 | 7000 | 0.2760 | 0.0717 |
| 0.0074 | 70.8 | 8000 | 0.3004 | 0.0680 |
| 0.0058 | 79.65 | 9000 | 0.3113 | 0.0650 |
| 0.0033 | 88.5 | 10000 | 0.3212 | 0.0636 |
### Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2
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