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-01
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-01

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: 0.1438
- Wer: 0.0916
- Cer: 0.0276

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.3099       | 1.0   | 67   | 3.7928          | 0.9875 | 0.9520 |
| 5.6597        | 2.0   | 134  | 2.8806          | 0.9976 | 0.9981 |
| 2.6541        | 3.0   | 201  | 0.7077          | 0.8102 | 0.2128 |
| 2.6541        | 4.0   | 268  | 0.1972          | 0.1515 | 0.0404 |
| 0.5065        | 5.0   | 335  | 0.1899          | 0.1118 | 0.0331 |
| 0.3081        | 6.0   | 402  | 0.1892          | 0.1017 | 0.0313 |
| 0.3081        | 7.0   | 469  | 0.1563          | 0.1094 | 0.0314 |
| 0.25          | 8.0   | 536  | 0.1683          | 0.0975 | 0.0299 |
| 0.2263        | 9.0   | 603  | 0.1672          | 0.0968 | 0.0303 |
| 0.2263        | 10.0  | 670  | 0.1524          | 0.0940 | 0.0281 |
| 0.1903        | 11.0  | 737  | 0.1438          | 0.0916 | 0.0276 |
| 0.1825        | 12.0  | 804  | 0.1577          | 0.0899 | 0.0280 |
| 0.1825        | 13.0  | 871  | 0.1519          | 0.0902 | 0.0274 |
| 0.166         | 14.0  | 938  | 0.1612          | 0.0937 | 0.0276 |
| 0.1965        | 15.0  | 1005 | 0.1592          | 0.0885 | 0.0282 |
| 0.1965        | 16.0  | 1072 | 0.1633          | 0.0916 | 0.0268 |
| 0.1597        | 17.0  | 1139 | 0.1685          | 0.0885 | 0.0269 |
| 0.1411        | 18.0  | 1206 | 0.1679          | 0.0909 | 0.0274 |
| 0.1411        | 19.0  | 1273 | 0.1677          | 0.0892 | 0.0271 |
| 0.1169        | 20.0  | 1340 | 0.1534          | 0.0860 | 0.0256 |
| 0.1169        | 21.0  | 1407 | 0.1726          | 0.0909 | 0.0266 |
| 0.1169        | 22.0  | 1474 | 0.1597          | 0.0871 | 0.0261 |
| 0.1232        | 23.0  | 1541 | 0.1602          | 0.0930 | 0.0273 |
| 0.1067        | 24.0  | 1608 | 0.1690          | 0.0965 | 0.0273 |
| 0.1067        | 25.0  | 1675 | 0.1610          | 0.0920 | 0.0273 |
| 0.0947        | 26.0  | 1742 | 0.1721          | 0.0885 | 0.0269 |
| 0.0945        | 27.0  | 1809 | 0.1738          | 0.0874 | 0.0265 |
| 0.0945        | 28.0  | 1876 | 0.1728          | 0.0906 | 0.0265 |
| 0.0976        | 29.0  | 1943 | 0.1853          | 0.0878 | 0.0263 |
| 0.0872        | 30.0  | 2010 | 0.1626          | 0.0874 | 0.0259 |
| 0.0872        | 31.0  | 2077 | 0.1688          | 0.0860 | 0.0261 |


### Framework versions

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