---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: XLS-R_Jibbali_lang
  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. -->

# XLS-R_Jibbali_lang

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1714
- Wer: 0.1941

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.1473       | 0.99  | 56   | 11.0651         | 1.0    |
| 3.9177        | 2.0   | 113  | 3.4720          | 1.0    |
| 3.1902        | 2.99  | 169  | 3.1574          | 1.0    |
| 3.1711        | 4.0   | 226  | 3.1379          | 1.0    |
| 3.1491        | 4.99  | 282  | 3.1154          | 1.0    |
| 3.1449        | 6.0   | 339  | 3.0533          | 1.0    |
| 2.9214        | 6.99  | 395  | 2.7533          | 1.0    |
| 1.9003        | 8.0   | 452  | 1.4168          | 0.9291 |
| 0.6151        | 8.99  | 508  | 0.3110          | 0.3224 |
| 0.2125        | 10.0  | 565  | 0.2170          | 0.2145 |
| 0.1754        | 10.99 | 621  | 0.1987          | 0.2069 |
| 0.1688        | 12.0  | 678  | 0.1870          | 0.1985 |
| 0.1012        | 12.99 | 734  | 0.1856          | 0.1908 |
| 0.1157        | 14.0  | 791  | 0.1906          | 0.2025 |
| 0.1427        | 14.99 | 847  | 0.1844          | 0.1937 |
| 0.0513        | 16.0  | 904  | 0.1852          | 0.1915 |
| 0.1403        | 16.99 | 960  | 0.1713          | 0.1944 |
| 0.1119        | 18.0  | 1017 | 0.1610          | 0.1974 |
| 0.1034        | 18.99 | 1073 | 0.1697          | 0.1944 |
| 0.0428        | 19.82 | 1120 | 0.1714          | 0.1941 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2