---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-mecita-coraa-portuguese-aug-random-all-03
  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-large-xlsr-mecita-coraa-portuguese-aug-random-all-03

This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1357
- Wer: 0.0844
- Cer: 0.0268

## 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: 3e-05
- 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
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.883         | 1.0   | 514   | 2.5884          | 0.9955 | 0.9943 |
| 0.9481        | 2.0   | 1029  | 0.2560          | 0.1474 | 0.0436 |
| 0.742         | 3.0   | 1543  | 0.1802          | 0.1098 | 0.0340 |
| 0.625         | 4.0   | 2058  | 0.1590          | 0.0975 | 0.0308 |
| 0.6001        | 5.0   | 2572  | 0.1486          | 0.0887 | 0.0292 |
| 0.5208        | 6.0   | 3087  | 0.1424          | 0.0918 | 0.0284 |
| 0.4857        | 7.0   | 3601  | 0.1357          | 0.0844 | 0.0268 |
| 0.4458        | 8.0   | 4116  | 0.1375          | 0.0882 | 0.0317 |
| 0.4158        | 9.0   | 4630  | 0.1411          | 0.0839 | 0.0303 |
| 0.3915        | 10.0  | 5145  | 0.1457          | 0.0915 | 0.0319 |
| 0.3898        | 11.0  | 5659  | 0.1464          | 0.0870 | 0.0310 |
| 0.3562        | 12.0  | 6174  | 0.1500          | 0.0875 | 0.0314 |
| 0.3619        | 13.0  | 6688  | 0.1523          | 0.0877 | 0.0313 |
| 0.3283        | 14.0  | 7203  | 0.1473          | 0.0856 | 0.0290 |
| 0.3196        | 15.0  | 7717  | 0.1443          | 0.0844 | 0.0299 |
| 0.3165        | 16.0  | 8232  | 0.1413          | 0.0813 | 0.0283 |
| 0.2954        | 17.0  | 8746  | 0.1451          | 0.0825 | 0.0283 |
| 0.293         | 18.0  | 9261  | 0.1539          | 0.0822 | 0.0286 |
| 0.2821        | 19.0  | 9775  | 0.1552          | 0.0844 | 0.0296 |
| 0.2893        | 20.0  | 10290 | 0.1484          | 0.0820 | 0.0285 |
| 0.2609        | 21.0  | 10804 | 0.1636          | 0.0851 | 0.0307 |
| 0.2526        | 22.0  | 11319 | 0.1520          | 0.0856 | 0.0292 |
| 0.2571        | 23.0  | 11833 | 0.1449          | 0.0851 | 0.0291 |
| 0.2486        | 24.0  | 12348 | 0.1574          | 0.0865 | 0.0307 |
| 0.2501        | 25.0  | 12862 | 0.1490          | 0.0856 | 0.0295 |
| 0.2525        | 26.0  | 13377 | 0.1508          | 0.0827 | 0.0294 |
| 0.2452        | 27.0  | 13891 | 0.1511          | 0.0808 | 0.0290 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.13.3