transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-1b-mecita-portuguese-all-clean-10
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-10

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: 0.1514
- Wer: 0.0869
- Cer: 0.0287

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 22.1247       | 1.0   | 67   | 2.8766          | 1.0    | 1.0    |
| 4.814         | 2.0   | 134  | 0.3766          | 0.2506 | 0.0658 |
| 0.8372        | 3.0   | 201  | 0.2164          | 0.1177 | 0.0368 |
| 0.8372        | 4.0   | 268  | 0.1876          | 0.1106 | 0.0331 |
| 0.294         | 5.0   | 335  | 0.1951          | 0.1011 | 0.0325 |
| 0.2405        | 6.0   | 402  | 0.1718          | 0.0957 | 0.0300 |
| 0.2405        | 7.0   | 469  | 0.1647          | 0.0947 | 0.0296 |
| 0.1998        | 8.0   | 536  | 0.1709          | 0.0950 | 0.0305 |
| 0.1946        | 9.0   | 603  | 0.1730          | 0.0906 | 0.0299 |
| 0.1946        | 10.0  | 670  | 0.1695          | 0.0876 | 0.0289 |
| 0.1938        | 11.0  | 737  | 0.1649          | 0.0852 | 0.0282 |
| 0.1667        | 12.0  | 804  | 0.1644          | 0.0869 | 0.0280 |
| 0.1667        | 13.0  | 871  | 0.1534          | 0.0842 | 0.0275 |
| 0.163         | 14.0  | 938  | 0.1514          | 0.0869 | 0.0287 |
| 0.1568        | 15.0  | 1005 | 0.1583          | 0.0873 | 0.0287 |
| 0.1568        | 16.0  | 1072 | 0.1655          | 0.0856 | 0.0283 |
| 0.1465        | 17.0  | 1139 | 0.1691          | 0.0859 | 0.0272 |
| 0.138         | 18.0  | 1206 | 0.1777          | 0.0906 | 0.0290 |
| 0.138         | 19.0  | 1273 | 0.1652          | 0.0859 | 0.0280 |
| 0.1251        | 20.0  | 1340 | 0.1715          | 0.0856 | 0.0275 |
| 0.136         | 21.0  | 1407 | 0.1614          | 0.0832 | 0.0267 |
| 0.136         | 22.0  | 1474 | 0.1579          | 0.0805 | 0.0262 |
| 0.1179        | 23.0  | 1541 | 0.1777          | 0.0842 | 0.0277 |
| 0.1029        | 24.0  | 1608 | 0.1761          | 0.0825 | 0.0274 |
| 0.1029        | 25.0  | 1675 | 0.1665          | 0.0839 | 0.0275 |
| 0.1139        | 26.0  | 1742 | 0.1821          | 0.0801 | 0.0279 |
| 0.1019        | 27.0  | 1809 | 0.1807          | 0.0856 | 0.0279 |
| 0.1019        | 28.0  | 1876 | 0.1883          | 0.0812 | 0.0273 |
| 0.0911        | 29.0  | 1943 | 0.1904          | 0.0808 | 0.0272 |
| 0.0919        | 30.0  | 2010 | 0.1839          | 0.0862 | 0.0285 |
| 0.0919        | 31.0  | 2077 | 0.1902          | 0.0852 | 0.0282 |
| 0.084         | 32.0  | 2144 | 0.1934          | 0.0822 | 0.0275 |
| 0.0809        | 33.0  | 2211 | 0.2050          | 0.0822 | 0.0282 |
| 0.0809        | 34.0  | 2278 | 0.1955          | 0.0832 | 0.0281 |


### Framework versions

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