---
library_name: transformers
license: apache-2.0
base_model: lejonck/xlsr53-ptbr-2
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xlsr53-ptbr-3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: pt
      split: None
      args: pt
    metrics:
    - name: Wer
      type: wer
      value: 0.98989898989899
---

<!-- 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. -->

# xlsr53-ptbr-3

This model is a fine-tuned version of [lejonck/xlsr53-ptbr-2](https://huggingface.co/lejonck/xlsr53-ptbr-2) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7741
- Wer: 0.9899
- Cer: 10.8976

## 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 5.1364        | 1.0   | 250  | 4.1358          | 0.9949 | 10.6432 |
| 5.0838        | 2.0   | 500  | 4.0543          | 0.9941 | 10.5248 |
| 4.3622        | 3.0   | 750  | 3.9937          | 0.9924 | 10.2184 |
| 4.1477        | 4.0   | 1000 | 3.9178          | 0.9924 | 10.2848 |
| 4.4121        | 5.0   | 1250 | 3.8755          | 0.9924 | 10.3005 |
| 3.9327        | 6.0   | 1500 | 3.8408          | 0.9907 | 10.4761 |
| 4.0681        | 7.0   | 1750 | 3.8321          | 0.9916 | 10.7547 |
| 3.9356        | 8.0   | 2000 | 3.7912          | 0.9916 | 10.5872 |
| 4.3374        | 9.0   | 2250 | 3.7739          | 0.9899 | 10.6934 |
| 3.7845        | 10.0  | 2500 | 3.7741          | 0.9899 | 10.8360 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0