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---
library_name: transformers
license: apache-2.0
base_model: elgeish/wav2vec2-large-xlsr-53-arabic
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: elgeish-wav2vec2-arabic-fine-tuning_6P
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. -->
# elgeish-wav2vec2-arabic-fine-tuning_6P
This model is a fine-tuned version of [elgeish/wav2vec2-large-xlsr-53-arabic](https://huggingface.co/elgeish/wav2vec2-large-xlsr-53-arabic) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4511
- Wer: 0.4936
## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 33.2595 | 0.8 | 100 | 10.7960 | 1.0 |
| 14.3333 | 1.6 | 200 | 8.1978 | 1.0 |
| 4.8209 | 2.4 | 300 | 3.2571 | 1.0 |
| 3.1719 | 3.2 | 400 | 3.1181 | 1.0 |
| 3.0831 | 4.0 | 500 | 3.0458 | 1.0 |
| 2.5752 | 4.8 | 600 | 1.5734 | 1.0 |
| 1.4728 | 5.6 | 700 | 1.2424 | 0.8933 |
| 1.1457 | 6.4 | 800 | 1.0115 | 0.8471 |
| 1.0544 | 7.2 | 900 | 1.1768 | 0.8726 |
| 1.065 | 8.0 | 1000 | 1.1300 | 0.8232 |
| 0.9797 | 8.8 | 1100 | 1.0768 | 0.8248 |
| 0.8787 | 9.6 | 1200 | 1.2050 | 0.8519 |
| 0.7859 | 10.4 | 1300 | 0.8281 | 0.7564 |
| 0.7123 | 11.2 | 1400 | 0.8351 | 0.7086 |
| 0.6248 | 12.0 | 1500 | 0.9252 | 0.7834 |
| 0.5965 | 12.8 | 1600 | 0.6848 | 0.6879 |
| 0.4854 | 13.6 | 1700 | 0.6451 | 0.6322 |
| 0.4371 | 14.4 | 1800 | 0.5714 | 0.6003 |
| 0.3767 | 15.2 | 1900 | 0.6853 | 0.6178 |
| 0.3472 | 16.0 | 2000 | 0.6118 | 0.6035 |
| 0.3105 | 16.8 | 2100 | 0.5476 | 0.5764 |
| 0.2706 | 17.6 | 2200 | 0.4950 | 0.5446 |
| 0.2378 | 18.4 | 2300 | 0.5300 | 0.5096 |
| 0.2028 | 19.2 | 2400 | 0.4686 | 0.5048 |
| 0.1851 | 20.0 | 2500 | 0.4511 | 0.4936 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3
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