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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-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: 0.1350
- Wer: 0.0841
- Cer: 0.0261

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.65         | 1.0   | 86   | 3.1940          | 1.0    | 1.0    |
| 8.1771        | 2.0   | 172  | 2.9853          | 1.0    | 1.0    |
| 3.0358        | 3.0   | 258  | 2.8955          | 1.0    | 1.0    |
| 2.9359        | 4.0   | 344  | 2.9086          | 1.0    | 1.0    |
| 2.9026        | 5.0   | 430  | 2.6946          | 0.9998 | 0.9998 |
| 2.4934        | 6.0   | 516  | 0.9106          | 0.4944 | 0.1257 |
| 1.1576        | 7.0   | 602  | 0.4618          | 0.2291 | 0.0627 |
| 1.1576        | 8.0   | 688  | 0.3427          | 0.1871 | 0.0538 |
| 0.7498        | 9.0   | 774  | 0.2838          | 0.1673 | 0.0480 |
| 0.5493        | 10.0  | 860  | 0.2504          | 0.1490 | 0.0442 |
| 0.4735        | 11.0  | 946  | 0.2318          | 0.1388 | 0.0412 |
| 0.4183        | 12.0  | 1032 | 0.2174          | 0.1215 | 0.0374 |
| 0.3924        | 13.0  | 1118 | 0.2019          | 0.1127 | 0.0357 |
| 0.3497        | 14.0  | 1204 | 0.1876          | 0.1112 | 0.0343 |
| 0.3497        | 15.0  | 1290 | 0.1865          | 0.1110 | 0.0351 |
| 0.3335        | 16.0  | 1376 | 0.1759          | 0.1065 | 0.0328 |
| 0.3259        | 17.0  | 1462 | 0.1718          | 0.0941 | 0.0310 |
| 0.2822        | 18.0  | 1548 | 0.1664          | 0.0965 | 0.0307 |
| 0.2689        | 19.0  | 1634 | 0.1638          | 0.0951 | 0.0302 |
| 0.262         | 20.0  | 1720 | 0.1616          | 0.0937 | 0.0307 |
| 0.2623        | 21.0  | 1806 | 0.1574          | 0.0927 | 0.0299 |
| 0.2623        | 22.0  | 1892 | 0.1559          | 0.0944 | 0.0306 |
| 0.2344        | 23.0  | 1978 | 0.1538          | 0.0920 | 0.0293 |
| 0.2315        | 24.0  | 2064 | 0.1533          | 0.0927 | 0.0298 |
| 0.2411        | 25.0  | 2150 | 0.1520          | 0.0908 | 0.0294 |
| 0.2102        | 26.0  | 2236 | 0.1496          | 0.0922 | 0.0297 |
| 0.2115        | 27.0  | 2322 | 0.1473          | 0.0979 | 0.0298 |
| 0.2139        | 28.0  | 2408 | 0.1496          | 0.0958 | 0.0300 |
| 0.2139        | 29.0  | 2494 | 0.1446          | 0.0903 | 0.0289 |
| 0.2218        | 30.0  | 2580 | 0.1482          | 0.0913 | 0.0291 |
| 0.1982        | 31.0  | 2666 | 0.1439          | 0.0891 | 0.0284 |
| 0.196         | 32.0  | 2752 | 0.1428          | 0.0934 | 0.0286 |
| 0.1846        | 33.0  | 2838 | 0.1404          | 0.0906 | 0.0281 |
| 0.1873        | 34.0  | 2924 | 0.1395          | 0.0856 | 0.0272 |
| 0.1854        | 35.0  | 3010 | 0.1354          | 0.0846 | 0.0268 |
| 0.1854        | 36.0  | 3096 | 0.1359          | 0.0858 | 0.0271 |
| 0.1851        | 37.0  | 3182 | 0.1356          | 0.0903 | 0.0276 |
| 0.1733        | 38.0  | 3268 | 0.1380          | 0.0851 | 0.0270 |
| 0.1781        | 39.0  | 3354 | 0.1359          | 0.0813 | 0.0258 |
| 0.1821        | 40.0  | 3440 | 0.1383          | 0.0863 | 0.0274 |
| 0.1724        | 41.0  | 3526 | 0.1377          | 0.0822 | 0.0265 |
| 0.1591        | 42.0  | 3612 | 0.1379          | 0.0844 | 0.0266 |
| 0.1591        | 43.0  | 3698 | 0.1350          | 0.0841 | 0.0261 |
| 0.168         | 44.0  | 3784 | 0.1362          | 0.0846 | 0.0265 |
| 0.162         | 45.0  | 3870 | 0.1353          | 0.0820 | 0.0266 |
| 0.145         | 46.0  | 3956 | 0.1414          | 0.0849 | 0.0270 |
| 0.1639        | 47.0  | 4042 | 0.1400          | 0.0837 | 0.0266 |
| 0.1572        | 48.0  | 4128 | 0.1387          | 0.0815 | 0.0261 |
| 0.14          | 49.0  | 4214 | 0.1384          | 0.0822 | 0.0258 |
| 0.1473        | 50.0  | 4300 | 0.1399          | 0.0827 | 0.0265 |
| 0.1473        | 51.0  | 4386 | 0.1408          | 0.0822 | 0.0265 |
| 0.1722        | 52.0  | 4472 | 0.1411          | 0.0851 | 0.0267 |
| 0.1518        | 53.0  | 4558 | 0.1410          | 0.0860 | 0.0273 |
| 0.1506        | 54.0  | 4644 | 0.1403          | 0.0858 | 0.0270 |
| 0.1442        | 55.0  | 4730 | 0.1380          | 0.0832 | 0.0262 |
| 0.1427        | 56.0  | 4816 | 0.1395          | 0.0815 | 0.0265 |
| 0.132         | 57.0  | 4902 | 0.1384          | 0.0813 | 0.0259 |
| 0.132         | 58.0  | 4988 | 0.1353          | 0.0818 | 0.0261 |
| 0.1374        | 59.0  | 5074 | 0.1405          | 0.0834 | 0.0265 |
| 0.1318        | 60.0  | 5160 | 0.1383          | 0.0811 | 0.0258 |
| 0.1339        | 61.0  | 5246 | 0.1386          | 0.0813 | 0.0261 |
| 0.1346        | 62.0  | 5332 | 0.1399          | 0.0801 | 0.0253 |
| 0.1261        | 63.0  | 5418 | 0.1430          | 0.0832 | 0.0263 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-03", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us