---
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
  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: 0.0365
- Per: 0.0138

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.3526        | 1.0   | 102  | 2.1537          | 1.0    |
| 2.0368        | 2.0   | 204  | 2.0887          | 1.0    |
| 2.0267        | 3.0   | 306  | 2.0675          | 1.0    |
| 1.9965        | 4.0   | 408  | 1.9867          | 0.9940 |
| 1.9372        | 5.0   | 510  | 1.8724          | 0.9825 |
| 1.7146        | 6.0   | 612  | 1.6606          | 0.9913 |
| 1.6576        | 7.0   | 714  | 1.6004          | 0.9933 |
| 1.4857        | 8.0   | 816  | 1.3504          | 0.9871 |
| 1.117         | 9.0   | 918  | 0.8836          | 0.8882 |
| 0.6447        | 10.0  | 1020 | 0.4553          | 0.4092 |
| 0.3553        | 11.0  | 1122 | 0.2485          | 0.1743 |
| 0.2193        | 12.0  | 1224 | 0.1664          | 0.0711 |
| 0.1677        | 13.0  | 1326 | 0.1392          | 0.0621 |
| 0.1317        | 14.0  | 1428 | 0.1072          | 0.0418 |
| 0.1203        | 15.0  | 1530 | 0.0975          | 0.0361 |
| 0.1079        | 16.0  | 1632 | 0.0936          | 0.0314 |
| 0.0902        | 17.0  | 1734 | 0.0762          | 0.0254 |
| 0.0835        | 18.0  | 1836 | 0.0609          | 0.0229 |
| 0.0691        | 19.0  | 1938 | 0.0592          | 0.0223 |
| 0.0665        | 20.0  | 2040 | 0.0601          | 0.0229 |
| 0.0599        | 21.0  | 2142 | 0.0469          | 0.0179 |
| 0.0545        | 22.0  | 2244 | 0.0520          | 0.0203 |
| 0.047         | 23.0  | 2346 | 0.0450          | 0.0163 |
| 0.0409        | 24.0  | 2448 | 0.0449          | 0.0181 |
| 0.0401        | 25.0  | 2550 | 0.0431          | 0.0160 |
| 0.0403        | 26.0  | 2652 | 0.0419          | 0.0164 |
| 0.0351        | 27.0  | 2754 | 0.0360          | 0.0143 |
| 0.0324        | 28.0  | 2856 | 0.0386          | 0.0145 |
| 0.0311        | 29.0  | 2958 | 0.0367          | 0.0139 |
| 0.028         | 30.0  | 3060 | 0.0365          | 0.0138 |


### Framework versions

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