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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-09

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: 0.1745
- Wer: 0.0933
- Cer: 0.0337

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.0008       | 1.0   | 86   | 3.2501          | 1.0    | 1.0    |
| 7.6102        | 2.0   | 172  | 2.9776          | 1.0    | 1.0    |
| 3.0591        | 3.0   | 258  | 2.9323          | 1.0    | 1.0    |
| 2.9269        | 4.0   | 344  | 2.8718          | 1.0    | 1.0    |
| 2.8123        | 5.0   | 430  | 1.5130          | 0.9998 | 0.3438 |
| 1.6357        | 6.0   | 516  | 0.6038          | 0.3162 | 0.0853 |
| 0.8768        | 7.0   | 602  | 0.4187          | 0.2019 | 0.0613 |
| 0.8768        | 8.0   | 688  | 0.3472          | 0.1785 | 0.0557 |
| 0.6487        | 9.0   | 774  | 0.3102          | 0.1609 | 0.0526 |
| 0.5078        | 10.0  | 860  | 0.2706          | 0.1496 | 0.0486 |
| 0.4539        | 11.0  | 946  | 0.2527          | 0.1334 | 0.0455 |
| 0.4302        | 12.0  | 1032 | 0.2424          | 0.1234 | 0.0434 |
| 0.359         | 13.0  | 1118 | 0.2259          | 0.1236 | 0.0416 |
| 0.3396        | 14.0  | 1204 | 0.2319          | 0.1167 | 0.0417 |
| 0.3396        | 15.0  | 1290 | 0.2139          | 0.1172 | 0.0405 |
| 0.3103        | 16.0  | 1376 | 0.2138          | 0.1148 | 0.0400 |
| 0.2993        | 17.0  | 1462 | 0.2122          | 0.1079 | 0.0391 |
| 0.2879        | 18.0  | 1548 | 0.2020          | 0.1098 | 0.0388 |
| 0.2795        | 19.0  | 1634 | 0.1976          | 0.1048 | 0.0372 |
| 0.2554        | 20.0  | 1720 | 0.1942          | 0.1007 | 0.0366 |
| 0.2517        | 21.0  | 1806 | 0.2004          | 0.1007 | 0.0366 |
| 0.2517        | 22.0  | 1892 | 0.1963          | 0.1057 | 0.0374 |
| 0.2206        | 23.0  | 1978 | 0.1960          | 0.1002 | 0.0356 |
| 0.2267        | 24.0  | 2064 | 0.1866          | 0.1026 | 0.0365 |
| 0.2448        | 25.0  | 2150 | 0.1861          | 0.1005 | 0.0364 |
| 0.2247        | 26.0  | 2236 | 0.1815          | 0.1024 | 0.0361 |
| 0.1998        | 27.0  | 2322 | 0.1873          | 0.1010 | 0.0355 |
| 0.2065        | 28.0  | 2408 | 0.1865          | 0.0967 | 0.0348 |
| 0.2065        | 29.0  | 2494 | 0.1864          | 0.1    | 0.0357 |
| 0.2061        | 30.0  | 2580 | 0.1872          | 0.0959 | 0.0352 |
| 0.2018        | 31.0  | 2666 | 0.1856          | 0.0998 | 0.0358 |
| 0.179         | 32.0  | 2752 | 0.1805          | 0.0964 | 0.0343 |
| 0.1827        | 33.0  | 2838 | 0.1833          | 0.0955 | 0.0345 |
| 0.1886        | 34.0  | 2924 | 0.1859          | 0.0971 | 0.0342 |
| 0.1696        | 35.0  | 3010 | 0.1889          | 0.0981 | 0.0348 |
| 0.1696        | 36.0  | 3096 | 0.1829          | 0.0979 | 0.0345 |
| 0.1843        | 37.0  | 3182 | 0.1811          | 0.0945 | 0.0343 |
| 0.1595        | 38.0  | 3268 | 0.1807          | 0.0952 | 0.0348 |
| 0.1804        | 39.0  | 3354 | 0.1799          | 0.0971 | 0.0349 |
| 0.1837        | 40.0  | 3440 | 0.1815          | 0.0950 | 0.0341 |
| 0.1574        | 41.0  | 3526 | 0.1787          | 0.0971 | 0.0346 |
| 0.1594        | 42.0  | 3612 | 0.1833          | 0.0945 | 0.0340 |
| 0.1594        | 43.0  | 3698 | 0.1810          | 0.0902 | 0.0331 |
| 0.1537        | 44.0  | 3784 | 0.1832          | 0.0938 | 0.0339 |
| 0.1632        | 45.0  | 3870 | 0.1779          | 0.0933 | 0.0332 |
| 0.1607        | 46.0  | 3956 | 0.1781          | 0.0945 | 0.0340 |
| 0.1385        | 47.0  | 4042 | 0.1793          | 0.0940 | 0.0336 |
| 0.1522        | 48.0  | 4128 | 0.1750          | 0.0912 | 0.0326 |
| 0.159         | 49.0  | 4214 | 0.1848          | 0.0936 | 0.0336 |
| 0.1405        | 50.0  | 4300 | 0.1745          | 0.0933 | 0.0337 |
| 0.1405        | 51.0  | 4386 | 0.1812          | 0.0926 | 0.0339 |
| 0.1379        | 52.0  | 4472 | 0.1800          | 0.0926 | 0.0337 |
| 0.1421        | 53.0  | 4558 | 0.1827          | 0.0950 | 0.0341 |
| 0.1262        | 54.0  | 4644 | 0.1774          | 0.0943 | 0.0334 |
| 0.1535        | 55.0  | 4730 | 0.1796          | 0.0945 | 0.0335 |
| 0.1339        | 56.0  | 4816 | 0.1761          | 0.0938 | 0.0334 |
| 0.146         | 57.0  | 4902 | 0.1814          | 0.0933 | 0.0334 |
| 0.146         | 58.0  | 4988 | 0.1784          | 0.0938 | 0.0327 |
| 0.1363        | 59.0  | 5074 | 0.1754          | 0.0926 | 0.0323 |
| 0.1352        | 60.0  | 5160 | 0.1786          | 0.0952 | 0.0336 |
| 0.1498        | 61.0  | 5246 | 0.1801          | 0.0940 | 0.0329 |
| 0.1255        | 62.0  | 5332 | 0.1801          | 0.0967 | 0.0338 |
| 0.1272        | 63.0  | 5418 | 0.1803          | 0.0928 | 0.0328 |
| 0.1187        | 64.0  | 5504 | 0.1795          | 0.0945 | 0.0329 |
| 0.1187        | 65.0  | 5590 | 0.1835          | 0.0936 | 0.0328 |
| 0.1311        | 66.0  | 5676 | 0.1802          | 0.0940 | 0.0328 |
| 0.1427        | 67.0  | 5762 | 0.1790          | 0.0933 | 0.0331 |
| 0.1089        | 68.0  | 5848 | 0.1774          | 0.0931 | 0.0332 |
| 0.1203        | 69.0  | 5934 | 0.1823          | 0.0919 | 0.0330 |
| 0.1135        | 70.0  | 6020 | 0.1817          | 0.0940 | 0.0335 |


### 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-09", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us