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-06
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-06

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: 0.1389
- Wer: 0.0835
- Cer: 0.0248

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 31.447        | 1.0   | 86   | 2.9090          | 1.0    | 1.0    |
| 4.5778        | 2.0   | 172  | 0.3360          | 0.2277 | 0.0626 |
| 1.5152        | 3.0   | 258  | 0.2050          | 0.1148 | 0.0339 |
| 0.4121        | 4.0   | 344  | 0.1797          | 0.1011 | 0.0305 |
| 0.3139        | 5.0   | 430  | 0.1723          | 0.1021 | 0.0303 |
| 0.272         | 6.0   | 516  | 0.1598          | 0.0947 | 0.0288 |
| 0.2382        | 7.0   | 602  | 0.1556          | 0.0977 | 0.0286 |
| 0.2382        | 8.0   | 688  | 0.1418          | 0.0891 | 0.0264 |
| 0.2337        | 9.0   | 774  | 0.1431          | 0.0930 | 0.0270 |
| 0.2015        | 10.0  | 860  | 0.1443          | 0.0911 | 0.0268 |
| 0.1943        | 11.0  | 946  | 0.1458          | 0.0879 | 0.0260 |
| 0.1815        | 12.0  | 1032 | 0.1421          | 0.0849 | 0.0263 |
| 0.1669        | 13.0  | 1118 | 0.1389          | 0.0835 | 0.0248 |
| 0.1555        | 14.0  | 1204 | 0.1468          | 0.0825 | 0.0260 |
| 0.1555        | 15.0  | 1290 | 0.1471          | 0.0823 | 0.0255 |
| 0.1631        | 16.0  | 1376 | 0.1580          | 0.0852 | 0.0267 |
| 0.1527        | 17.0  | 1462 | 0.1525          | 0.0820 | 0.0255 |
| 0.1339        | 18.0  | 1548 | 0.1566          | 0.0761 | 0.0238 |
| 0.1268        | 19.0  | 1634 | 0.1516          | 0.0783 | 0.0245 |
| 0.1209        | 20.0  | 1720 | 0.1558          | 0.0820 | 0.0260 |
| 0.1163        | 21.0  | 1806 | 0.1744          | 0.0820 | 0.0262 |
| 0.1163        | 22.0  | 1892 | 0.1576          | 0.0849 | 0.0256 |
| 0.1575        | 23.0  | 1978 | 0.1664          | 0.0803 | 0.0263 |
| 0.1242        | 24.0  | 2064 | 0.1567          | 0.0813 | 0.0246 |
| 0.1362        | 25.0  | 2150 | 0.1571          | 0.0761 | 0.0246 |
| 0.1237        | 26.0  | 2236 | 0.1519          | 0.0813 | 0.0249 |
| 0.0949        | 27.0  | 2322 | 0.1525          | 0.0845 | 0.0251 |
| 0.1034        | 28.0  | 2408 | 0.1677          | 0.0815 | 0.0253 |
| 0.1034        | 29.0  | 2494 | 0.1568          | 0.0803 | 0.0246 |
| 0.1111        | 30.0  | 2580 | 0.1576          | 0.0810 | 0.0247 |
| 0.0925        | 31.0  | 2666 | 0.1533          | 0.0852 | 0.0252 |
| 0.0988        | 32.0  | 2752 | 0.1676          | 0.0847 | 0.0254 |
| 0.0882        | 33.0  | 2838 | 0.1626          | 0.0791 | 0.0247 |


### Framework versions

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