---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-Arabic-phoneme-Experiment3
  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-Experiment3

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: 0.0054
- Per: 0.0179

## 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: 6
- 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: 30.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 11.0415       | 1.0   | 102  | 3.1505          | 1.0    |
| 3.1122        | 2.0   | 204  | 3.0968          | 1.0    |
| 3.0896        | 3.0   | 306  | 3.0042          | 1.0    |
| 2.953         | 4.0   | 408  | 2.8056          | 1.0    |
| 2.444         | 5.0   | 510  | 1.7510          | 0.6859 |
| 1.1295        | 6.0   | 612  | 0.3595          | 0.1672 |
| 0.3895        | 7.0   | 714  | 0.1119          | 0.0782 |
| 0.2175        | 8.0   | 816  | 0.0607          | 0.0477 |
| 0.1353        | 9.0   | 918  | 0.0317          | 0.0247 |
| 0.0946        | 10.0  | 1020 | 0.0288          | 0.0286 |
| 0.0835        | 11.0  | 1122 | 0.0291          | 0.0370 |
| 0.0673        | 12.0  | 1224 | 0.0231          | 0.0261 |
| 0.0583        | 13.0  | 1326 | 0.0181          | 0.0199 |
| 0.0444        | 14.0  | 1428 | 0.0190          | 0.0266 |
| 0.041         | 15.0  | 1530 | 0.0134          | 0.0254 |
| 0.0357        | 16.0  | 1632 | 0.0122          | 0.0233 |
| 0.0301        | 17.0  | 1734 | 0.0098          | 0.0338 |
| 0.0265        | 18.0  | 1836 | 0.0099          | 0.0241 |
| 0.0241        | 19.0  | 1938 | 0.0098          | 0.0207 |
| 0.0258        | 20.0  | 2040 | 0.0089          | 0.0203 |
| 0.0234        | 21.0  | 2142 | 0.0104          | 0.0242 |
| 0.0193        | 22.0  | 2244 | 0.0126          | 0.0301 |
| 0.0186        | 23.0  | 2346 | 0.0073          | 0.0274 |
| 0.0155        | 24.0  | 2448 | 0.0073          | 0.0238 |
| 0.0143        | 25.0  | 2550 | 0.0056          | 0.0164 |
| 0.0134        | 26.0  | 2652 | 0.0060          | 0.0199 |
| 0.012         | 27.0  | 2754 | 0.0052          | 0.0206 |
| 0.0122        | 28.0  | 2856 | 0.0054          | 0.0179 |
| 0.0105        | 29.0  | 2958 | 0.0055          | 0.0188 |
| 0.0098        | 30.0  | 3060 | 0.0054          | 0.0179 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3