---
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