---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-1b-mecita-portuguese-all-text-protecao_aos_pandas
  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-xlsr-1b-mecita-portuguese-all-text-protecao_aos_pandas

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-xls-r-1b-portuguese](https://huggingface.co/jonatasgrosman/wav2vec2-xls-r-1b-portuguese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1881
- Wer: 0.1139
- Cer: 0.0303

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 13.7229       | 0.93  | 7    | 4.8592          | 1.0    | 0.9996 |
| 13.7229       | 2.0   | 15   | 3.0023          | 1.0    | 1.0    |
| 13.7229       | 2.93  | 22   | 2.9290          | 1.0    | 1.0    |
| 13.7229       | 4.0   | 30   | 2.9842          | 1.0    | 1.0    |
| 13.7229       | 4.93  | 37   | 2.8453          | 1.0    | 1.0    |
| 13.7229       | 6.0   | 45   | 2.8120          | 1.0    | 1.0    |
| 13.7229       | 6.93  | 52   | 2.8162          | 1.0    | 1.0    |
| 13.7229       | 8.0   | 60   | 2.7843          | 1.0    | 1.0    |
| 13.7229       | 8.93  | 67   | 2.7823          | 1.0    | 1.0    |
| 13.7229       | 10.0  | 75   | 2.7434          | 1.0    | 1.0    |
| 13.7229       | 10.93 | 82   | 2.6364          | 1.0    | 1.0    |
| 13.7229       | 12.0  | 90   | 2.3797          | 0.9876 | 0.9861 |
| 13.7229       | 12.93 | 97   | 1.9516          | 0.9950 | 0.9771 |
| 3.3197        | 14.0  | 105  | 1.5396          | 1.0    | 0.7474 |
| 3.3197        | 14.93 | 112  | 1.1038          | 0.9950 | 0.4273 |
| 3.3197        | 16.0  | 120  | 0.6536          | 0.6733 | 0.1691 |
| 3.3197        | 16.93 | 127  | 0.4087          | 0.3218 | 0.0729 |
| 3.3197        | 18.0  | 135  | 0.3119          | 0.2252 | 0.0561 |
| 3.3197        | 18.93 | 142  | 0.2720          | 0.1757 | 0.0479 |
| 3.3197        | 20.0  | 150  | 0.2405          | 0.1584 | 0.0413 |
| 3.3197        | 20.93 | 157  | 0.2365          | 0.1584 | 0.0409 |
| 3.3197        | 22.0  | 165  | 0.2281          | 0.1510 | 0.0397 |
| 3.3197        | 22.93 | 172  | 0.1989          | 0.1361 | 0.0360 |
| 3.3197        | 24.0  | 180  | 0.2051          | 0.1287 | 0.0360 |
| 3.3197        | 24.93 | 187  | 0.2265          | 0.1287 | 0.0356 |
| 3.3197        | 26.0  | 195  | 0.2203          | 0.1287 | 0.0377 |
| 0.5589        | 26.93 | 202  | 0.2181          | 0.1213 | 0.0340 |
| 0.5589        | 28.0  | 210  | 0.2006          | 0.1238 | 0.0336 |
| 0.5589        | 28.93 | 217  | 0.1860          | 0.1213 | 0.0332 |
| 0.5589        | 30.0  | 225  | 0.1772          | 0.1114 | 0.0303 |
| 0.5589        | 30.93 | 232  | 0.1914          | 0.1238 | 0.0323 |
| 0.5589        | 32.0  | 240  | 0.1997          | 0.1238 | 0.0323 |
| 0.5589        | 32.93 | 247  | 0.1947          | 0.1262 | 0.0340 |
| 0.5589        | 34.0  | 255  | 0.2056          | 0.1213 | 0.0327 |
| 0.5589        | 34.93 | 262  | 0.1985          | 0.1213 | 0.0332 |
| 0.5589        | 36.0  | 270  | 0.2016          | 0.1213 | 0.0327 |
| 0.5589        | 36.93 | 277  | 0.1941          | 0.1139 | 0.0311 |
| 0.5589        | 38.0  | 285  | 0.1824          | 0.1238 | 0.0319 |
| 0.5589        | 38.93 | 292  | 0.1822          | 0.1089 | 0.0295 |
| 0.1503        | 40.0  | 300  | 0.1969          | 0.1163 | 0.0311 |
| 0.1503        | 40.93 | 307  | 0.1996          | 0.1163 | 0.0295 |
| 0.1503        | 42.0  | 315  | 0.1880          | 0.1089 | 0.0295 |
| 0.1503        | 42.93 | 322  | 0.2017          | 0.1312 | 0.0344 |
| 0.1503        | 44.0  | 330  | 0.1914          | 0.1163 | 0.0327 |
| 0.1503        | 44.93 | 337  | 0.1935          | 0.1163 | 0.0332 |
| 0.1503        | 46.0  | 345  | 0.1967          | 0.1139 | 0.0319 |
| 0.1503        | 46.93 | 352  | 0.1913          | 0.1064 | 0.0299 |
| 0.1503        | 48.0  | 360  | 0.1994          | 0.1114 | 0.0303 |
| 0.1503        | 48.93 | 367  | 0.1883          | 0.1089 | 0.0291 |
| 0.1503        | 50.0  | 375  | 0.1881          | 0.1139 | 0.0303 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.13.3