---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- automatic-speech-recognition
- Leonel-Maia/fulfulde-no0
- generated_from_trainer
metrics:
- wer
model-index:
- name: Wav2vec2-fula-no0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Wav2vec2-fula-no0

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the LEONEL-MAIA/FULFULDE-NO0 - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4407
- Wer: 0.5583
- Cer: 0.1549

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 60.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 0.5615        | 0.1970 | 500  | 0.6706          | 0.7329 | 0.2082 |
| 0.3606        | 0.3939 | 1000 | 0.5461          | 0.6352 | 0.1786 |
| 0.3103        | 0.5909 | 1500 | 0.4960          | 0.6026 | 0.1695 |
| 0.228         | 0.7879 | 2000 | 0.5087          | 0.5917 | 0.1635 |
| 0.2502        | 0.9848 | 2500 | 0.4720          | 0.5835 | 0.1648 |
| 0.2841        | 1.1816 | 3000 | 0.4652          | 0.6019 | 0.1701 |
| 0.2603        | 1.3786 | 3500 | 0.4726          | 0.5685 | 0.1588 |
| 0.2538        | 1.5755 | 4000 | 0.4538          | 0.5667 | 0.1573 |
| 0.2215        | 1.7725 | 4500 | 0.4649          | 0.5615 | 0.1581 |
| 0.2329        | 1.9695 | 5000 | 0.4407          | 0.5583 | 0.1549 |
| 0.2111        | 2.1662 | 5500 | 0.4677          | 0.5529 | 0.1542 |
| 0.2018        | 2.3632 | 6000 | 0.4574          | 0.5507 | 0.1531 |
| 0.2421        | 2.5602 | 6500 | 0.4417          | 0.5500 | 0.1528 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1