---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD-experiment2
  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-based-MDD-experiment2

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: 0.0434
- Per: 0.0207
- Wer: 0.0212

## 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    | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.4593        | 1.0   | 546   | 1.6587          | 0.9769 | 0.9819 |
| 1.7776        | 2.0   | 1093  | 1.5794          | 0.9995 | 0.9994 |
| 1.733         | 3.0   | 1640  | 1.5264          | 0.9998 | 0.9998 |
| 1.6734        | 4.0   | 2187  | 1.3536          | 0.9948 | 0.9831 |
| 1.5266        | 5.0   | 2733  | 0.8784          | 0.6903 | 0.7321 |
| 1.1705        | 6.0   | 3280  | 0.3408          | 0.2076 | 0.2568 |
| 0.8237        | 7.0   | 3827  | 0.1968          | 0.1045 | 0.1223 |
| 0.66          | 8.0   | 4374  | 0.1400          | 0.0756 | 0.0851 |
| 0.5747        | 9.0   | 4920  | 0.0954          | 0.0665 | 0.0659 |
| 0.5063        | 10.0  | 5467  | 0.0999          | 0.0645 | 0.0650 |
| 0.4641        | 11.0  | 6014  | 0.0800          | 0.0545 | 0.0572 |
| 0.4246        | 12.0  | 6561  | 0.0783          | 0.0512 | 0.0506 |
| 0.3957        | 13.0  | 7107  | 0.0780          | 0.0494 | 0.0516 |
| 0.3693        | 14.0  | 7654  | 0.0647          | 0.0393 | 0.0411 |
| 0.3517        | 15.0  | 8201  | 0.0597          | 0.0364 | 0.0370 |
| 0.3292        | 16.0  | 8748  | 0.0577          | 0.0356 | 0.0361 |
| 0.3079        | 17.0  | 9294  | 0.0573          | 0.0346 | 0.0362 |
| 0.2946        | 18.0  | 9841  | 0.0622          | 0.0350 | 0.0389 |
| 0.2735        | 19.0  | 10388 | 0.0525          | 0.0293 | 0.0300 |
| 0.2588        | 20.0  | 10935 | 0.0553          | 0.0254 | 0.0283 |
| 0.2477        | 21.0  | 11481 | 0.0479          | 0.0244 | 0.0259 |
| 0.2346        | 22.0  | 12028 | 0.0560          | 0.0280 | 0.0283 |
| 0.222         | 23.0  | 12575 | 0.0421          | 0.0242 | 0.0250 |
| 0.208         | 24.0  | 13122 | 0.0508          | 0.0240 | 0.0245 |
| 0.2002        | 25.0  | 13668 | 0.0435          | 0.0218 | 0.0223 |
| 0.1912        | 26.0  | 14215 | 0.0477          | 0.0225 | 0.0239 |
| 0.1823        | 27.0  | 14762 | 0.0414          | 0.0210 | 0.0214 |
| 0.1745        | 28.0  | 15309 | 0.0434          | 0.0212 | 0.0216 |
| 0.1703        | 29.0  | 15855 | 0.0427          | 0.0202 | 0.0212 |
| 0.163         | 29.96 | 16380 | 0.0434          | 0.0207 | 0.0212 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3