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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-07

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: 0.1382
- Wer: 0.0921
- Cer: 0.0289

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.6541       | 1.0   | 86   | 3.2004          | 1.0    | 1.0    |
| 7.0678        | 2.0   | 172  | 2.9330          | 1.0    | 1.0    |
| 3.0229        | 3.0   | 258  | 2.9009          | 1.0    | 1.0    |
| 2.931         | 4.0   | 344  | 2.9000          | 1.0    | 1.0    |
| 2.9177        | 5.0   | 430  | 2.8428          | 1.0    | 1.0    |
| 2.6907        | 6.0   | 516  | 1.2090          | 0.9756 | 0.2837 |
| 1.3248        | 7.0   | 602  | 0.5202          | 0.2478 | 0.0702 |
| 1.3248        | 8.0   | 688  | 0.3687          | 0.1941 | 0.0567 |
| 0.7818        | 9.0   | 774  | 0.3006          | 0.1641 | 0.0482 |
| 0.5879        | 10.0  | 860  | 0.2740          | 0.1586 | 0.0476 |
| 0.5164        | 11.0  | 946  | 0.2360          | 0.1508 | 0.0446 |
| 0.4796        | 12.0  | 1032 | 0.2204          | 0.1385 | 0.0423 |
| 0.4054        | 13.0  | 1118 | 0.2071          | 0.1337 | 0.0399 |
| 0.3639        | 14.0  | 1204 | 0.2009          | 0.1148 | 0.0365 |
| 0.3639        | 15.0  | 1290 | 0.1918          | 0.1201 | 0.0370 |
| 0.3318        | 16.0  | 1376 | 0.1841          | 0.1073 | 0.0342 |
| 0.3192        | 17.0  | 1462 | 0.1804          | 0.1064 | 0.0344 |
| 0.2857        | 18.0  | 1548 | 0.1783          | 0.1030 | 0.0336 |
| 0.2867        | 19.0  | 1634 | 0.1730          | 0.1037 | 0.0331 |
| 0.2703        | 20.0  | 1720 | 0.1643          | 0.0993 | 0.0323 |
| 0.2625        | 21.0  | 1806 | 0.1624          | 0.1030 | 0.0320 |
| 0.2625        | 22.0  | 1892 | 0.1676          | 0.1003 | 0.0319 |
| 0.255         | 23.0  | 1978 | 0.1610          | 0.1003 | 0.0317 |
| 0.241         | 24.0  | 2064 | 0.1628          | 0.0981 | 0.0314 |
| 0.2422        | 25.0  | 2150 | 0.1607          | 0.0967 | 0.0312 |
| 0.2293        | 26.0  | 2236 | 0.1582          | 0.0957 | 0.0311 |
| 0.2222        | 27.0  | 2322 | 0.1550          | 0.0948 | 0.0304 |
| 0.227         | 28.0  | 2408 | 0.1564          | 0.0960 | 0.0310 |
| 0.227         | 29.0  | 2494 | 0.1601          | 0.0984 | 0.0310 |
| 0.2193        | 30.0  | 2580 | 0.1506          | 0.0911 | 0.0293 |
| 0.197         | 31.0  | 2666 | 0.1519          | 0.0948 | 0.0303 |
| 0.2087        | 32.0  | 2752 | 0.1510          | 0.0933 | 0.0304 |
| 0.1868        | 33.0  | 2838 | 0.1515          | 0.0984 | 0.0313 |
| 0.2023        | 34.0  | 2924 | 0.1538          | 0.0906 | 0.0296 |
| 0.206         | 35.0  | 3010 | 0.1473          | 0.0945 | 0.0299 |
| 0.206         | 36.0  | 3096 | 0.1473          | 0.0892 | 0.0292 |
| 0.2013        | 37.0  | 3182 | 0.1418          | 0.0928 | 0.0293 |
| 0.1733        | 38.0  | 3268 | 0.1459          | 0.0882 | 0.0282 |
| 0.1813        | 39.0  | 3354 | 0.1474          | 0.0904 | 0.0288 |
| 0.1903        | 40.0  | 3440 | 0.1423          | 0.0916 | 0.0294 |
| 0.1599        | 41.0  | 3526 | 0.1444          | 0.0914 | 0.0292 |
| 0.1576        | 42.0  | 3612 | 0.1439          | 0.0904 | 0.0287 |
| 0.1576        | 43.0  | 3698 | 0.1495          | 0.0882 | 0.0287 |
| 0.1603        | 44.0  | 3784 | 0.1407          | 0.0909 | 0.0294 |
| 0.1726        | 45.0  | 3870 | 0.1413          | 0.0897 | 0.0289 |
| 0.1582        | 46.0  | 3956 | 0.1416          | 0.0892 | 0.0284 |
| 0.1622        | 47.0  | 4042 | 0.1416          | 0.0894 | 0.0280 |
| 0.1581        | 48.0  | 4128 | 0.1404          | 0.0887 | 0.0284 |
| 0.1606        | 49.0  | 4214 | 0.1396          | 0.0894 | 0.0284 |
| 0.1422        | 50.0  | 4300 | 0.1458          | 0.0892 | 0.0281 |
| 0.1422        | 51.0  | 4386 | 0.1411          | 0.0919 | 0.0293 |
| 0.1611        | 52.0  | 4472 | 0.1417          | 0.0919 | 0.0293 |
| 0.1354        | 53.0  | 4558 | 0.1462          | 0.0909 | 0.0291 |
| 0.1433        | 54.0  | 4644 | 0.1382          | 0.0921 | 0.0289 |
| 0.145         | 55.0  | 4730 | 0.1424          | 0.0948 | 0.0293 |
| 0.1418        | 56.0  | 4816 | 0.1441          | 0.0921 | 0.0295 |
| 0.1544        | 57.0  | 4902 | 0.1435          | 0.0950 | 0.0293 |
| 0.1544        | 58.0  | 4988 | 0.1437          | 0.0940 | 0.0292 |
| 0.1342        | 59.0  | 5074 | 0.1468          | 0.0921 | 0.0289 |
| 0.1398        | 60.0  | 5160 | 0.1491          | 0.0923 | 0.0293 |
| 0.1325        | 61.0  | 5246 | 0.1451          | 0.0919 | 0.0293 |
| 0.1496        | 62.0  | 5332 | 0.1466          | 0.0926 | 0.0290 |
| 0.1283        | 63.0  | 5418 | 0.1447          | 0.0892 | 0.0286 |
| 0.1275        | 64.0  | 5504 | 0.1431          | 0.0868 | 0.0276 |
| 0.1275        | 65.0  | 5590 | 0.1452          | 0.0856 | 0.0271 |
| 0.126         | 66.0  | 5676 | 0.1463          | 0.0919 | 0.0284 |
| 0.1404        | 67.0  | 5762 | 0.1470          | 0.0911 | 0.0283 |
| 0.1446        | 68.0  | 5848 | 0.1444          | 0.0914 | 0.0282 |
| 0.1357        | 69.0  | 5934 | 0.1443          | 0.0906 | 0.0275 |
| 0.1269        | 70.0  | 6020 | 0.1440          | 0.0894 | 0.0276 |
| 0.1333        | 71.0  | 6106 | 0.1457          | 0.0902 | 0.0275 |
| 0.1333        | 72.0  | 6192 | 0.1454          | 0.0880 | 0.0278 |
| 0.1355        | 73.0  | 6278 | 0.1407          | 0.0890 | 0.0275 |
| 0.1108        | 74.0  | 6364 | 0.1428          | 0.0928 | 0.0287 |


### 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-07", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us