---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-Arabic-phoneme
  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-large-xls-r-300m-Arabic-phoneme

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0955
- Per: 0.0852

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 250
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.5617        | 1.0   | 102  | 2.2924          | 1.0    |
| 2.2639        | 2.0   | 204  | 2.3079          | 1.0    |
| 2.3203        | 2.99  | 306  | 2.3406          | 1.0    |
| 2.2545        | 4.0   | 409  | 2.2614          | 1.0    |
| 2.1643        | 5.0   | 511  | 1.7664          | 1.0    |
| 1.7206        | 6.0   | 613  | 1.7111          | 1.0    |
| 1.7024        | 6.99  | 715  | 1.7146          | 1.0    |
| 1.719         | 8.0   | 818  | 1.7485          | 1.0    |
| 1.7268        | 9.0   | 920  | 1.7347          | 1.0    |
| 1.7042        | 10.0  | 1022 | 1.7078          | 1.0    |
| 1.6836        | 10.99 | 1124 | 1.6868          | 1.0    |
| 1.6719        | 12.0  | 1227 | 1.6798          | 1.0    |
| 1.6573        | 13.0  | 1329 | 1.6622          | 1.0    |
| 1.6353        | 14.0  | 1431 | 1.6339          | 1.0    |
| 1.6179        | 14.99 | 1533 | 1.5896          | 1.0    |
| 1.5669        | 16.0  | 1636 | 1.5226          | 0.9793 |
| 1.5276        | 17.0  | 1738 | 1.4972          | 0.9533 |
| 1.4857        | 18.0  | 1840 | 1.4075          | 0.9757 |
| 1.4144        | 18.99 | 1942 | 1.3158          | 0.9685 |
| 1.3073        | 20.0  | 2045 | 1.1385          | 0.9692 |
| 1.1651        | 21.0  | 2147 | 0.9220          | 0.9523 |
| 1.0036        | 22.0  | 2249 | 0.7287          | 0.8698 |
| 0.7561        | 22.99 | 2351 | 0.5178          | 0.5407 |
| 0.6271        | 24.0  | 2454 | 0.3903          | 0.4185 |
| 0.5033        | 25.0  | 2556 | 0.2525          | 0.2356 |
| 0.4183        | 26.0  | 2658 | 0.1868          | 0.1624 |
| 0.351         | 26.99 | 2760 | 0.1435          | 0.1200 |
| 0.3256        | 28.0  | 2863 | 0.1154          | 0.1035 |
| 0.2859        | 29.0  | 2965 | 0.0996          | 0.0849 |
| 0.2771        | 29.93 | 3060 | 0.0996          | 0.0910 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3