---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-1b-dutch
  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-xls-r-1b-dutch

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5441
- Wer: 0.4250

## 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: 0.00015
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.8501        | 0.55  | 100  | 2.9579          | 1.0000 |
| 2.8419        | 1.09  | 200  | 2.8602          | 0.9999 |
| 2.5211        | 1.64  | 300  | 2.1828          | 0.9998 |
| 1.7206        | 2.19  | 400  | 1.2938          | 0.8820 |
| 1.4862        | 2.73  | 500  | 1.1201          | 0.8171 |
| 1.2637        | 3.28  | 600  | 1.0254          | 0.8137 |
| 1.0777        | 3.83  | 700  | 0.8863          | 0.6970 |
| 1.1046        | 4.37  | 800  | 0.8367          | 0.6378 |
| 0.8848        | 4.92  | 900  | 0.7275          | 0.5733 |
| 0.8134        | 5.46  | 1000 | 0.6990          | 0.5406 |
| 0.9912        | 6.01  | 1100 | 0.6568          | 0.5436 |
| 0.6002        | 6.56  | 1200 | 0.6744          | 0.5144 |
| 0.5809        | 7.1   | 1300 | 0.6510          | 0.5122 |
| 1.0383        | 7.65  | 1400 | 0.6050          | 0.4985 |
| 0.6218        | 8.2   | 1500 | 0.6552          | 0.5096 |
| 1.004         | 8.74  | 1600 | 0.6137          | 0.4794 |
| 0.8444        | 9.29  | 1700 | 0.5866          | 0.4805 |
| 0.9496        | 9.84  | 1800 | 0.5898          | 0.4726 |
| 0.7157        | 10.38 | 1900 | 0.5993          | 0.4642 |
| 0.6619        | 10.93 | 2000 | 0.5908          | 0.4706 |
| 0.4023        | 11.48 | 2100 | 0.6007          | 0.4601 |
| 0.6407        | 12.02 | 2200 | 0.5682          | 0.4583 |
| 0.3774        | 12.57 | 2300 | 0.5581          | 0.4489 |
| 0.5975        | 13.11 | 2400 | 0.5645          | 0.4490 |
| 0.5601        | 13.66 | 2500 | 0.5594          | 0.4523 |
| 0.5614        | 14.21 | 2600 | 0.5666          | 0.4421 |
| 0.3612        | 14.75 | 2700 | 0.5481          | 0.4377 |
| 0.3519        | 15.3  | 2800 | 0.5526          | 0.4374 |
| 0.325         | 15.85 | 2900 | 0.5244          | 0.4321 |
| 0.2626        | 16.39 | 3000 | 0.5340          | 0.4285 |
| 0.2425        | 16.94 | 3100 | 0.5495          | 0.4291 |
| 0.2306        | 17.49 | 3200 | 0.5369          | 0.4267 |
| 0.2374        | 18.03 | 3300 | 0.5379          | 0.4249 |
| 0.256         | 18.58 | 3400 | 0.5417          | 0.4248 |
| 0.2035        | 19.13 | 3500 | 0.5435          | 0.4251 |
| 0.1819        | 19.67 | 3600 | 0.5441          | 0.4250 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.7.0+cu126
- Datasets 2.16.1
- Tokenizers 0.15.2