---
license: apache-2.0
base_model: jonatasgrosman/wav2vec2-xls-r-1b-portuguese
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-1b-portuguese-casa-civil-030124
  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-portuguese-casa-civil-030124

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-xls-r-1b-portuguese](https://huggingface.co/jonatasgrosman/wav2vec2-xls-r-1b-portuguese) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5479
- Wer: 0.1310

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 28.5913       | 2.0   | 100  | 1.2903          | 0.1460 |
| 1.1869        | 4.0   | 200  | 0.6083          | 0.1537 |
| 0.8173        | 6.0   | 300  | 0.7054          | 0.2217 |
| 0.7882        | 8.0   | 400  | 0.7377          | 0.2711 |
| 0.6783        | 10.0  | 500  | 0.7785          | 0.2321 |
| 0.5541        | 12.0  | 600  | 0.6881          | 0.2394 |
| 0.5104        | 14.0  | 700  | 0.7285          | 0.2270 |
| 0.344         | 16.0  | 800  | 0.6114          | 0.1991 |
| 0.304         | 18.0  | 900  | 0.5559          | 0.1906 |
| 0.2315        | 20.0  | 1000 | 0.6833          | 0.1727 |
| 0.2144        | 22.0  | 1100 | 0.5632          | 0.1695 |
| 0.1725        | 24.0  | 1200 | 0.5597          | 0.1463 |
| 0.1492        | 26.0  | 1300 | 0.5356          | 0.1472 |
| 0.118         | 28.0  | 1400 | 0.5499          | 0.1344 |
| 0.1083        | 30.0  | 1500 | 0.5479          | 0.1310 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0