
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-06

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: 0.1392
- Wer: 0.0798
- Cer: 0.0243

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 31.6615       | 1.0   | 86   | 3.2646          | 1.0    | 1.0    |
| 7.8415        | 2.0   | 172  | 3.0801          | 1.0    | 1.0    |
| 3.0608        | 3.0   | 258  | 2.9214          | 1.0    | 1.0    |
| 2.9354        | 4.0   | 344  | 2.9229          | 1.0    | 1.0    |
| 2.9026        | 5.0   | 430  | 2.9320          | 1.0    | 1.0    |
| 2.8635        | 6.0   | 516  | 2.4574          | 0.9983 | 0.9727 |
| 2.0591        | 7.0   | 602  | 0.8060          | 0.4813 | 0.1157 |
| 2.0591        | 8.0   | 688  | 0.4447          | 0.2110 | 0.0585 |
| 0.9117        | 9.0   | 774  | 0.3337          | 0.1755 | 0.0498 |
| 0.6246        | 10.0  | 860  | 0.2807          | 0.1432 | 0.0421 |
| 0.4919        | 11.0  | 946  | 0.2575          | 0.1439 | 0.0401 |
| 0.413         | 12.0  | 1032 | 0.2348          | 0.1273 | 0.0365 |
| 0.3808        | 13.0  | 1118 | 0.2238          | 0.1231 | 0.0361 |
| 0.3585        | 14.0  | 1204 | 0.2149          | 0.1092 | 0.0325 |
| 0.3585        | 15.0  | 1290 | 0.1988          | 0.1050 | 0.0314 |
| 0.304         | 16.0  | 1376 | 0.1870          | 0.1028 | 0.0307 |
| 0.3112        | 17.0  | 1462 | 0.1839          | 0.1035 | 0.0301 |
| 0.3277        | 18.0  | 1548 | 0.1832          | 0.1001 | 0.0297 |
| 0.2754        | 19.0  | 1634 | 0.1763          | 0.0984 | 0.0295 |
| 0.2773        | 20.0  | 1720 | 0.1685          | 0.0942 | 0.0277 |
| 0.2389        | 21.0  | 1806 | 0.1645          | 0.0938 | 0.0280 |
| 0.2389        | 22.0  | 1892 | 0.1685          | 0.0947 | 0.0286 |
| 0.234         | 23.0  | 1978 | 0.1632          | 0.0923 | 0.0278 |
| 0.2385        | 24.0  | 2064 | 0.1655          | 0.0898 | 0.0277 |
| 0.2359        | 25.0  | 2150 | 0.1561          | 0.0884 | 0.0265 |
| 0.2326        | 26.0  | 2236 | 0.1535          | 0.0903 | 0.0266 |
| 0.2189        | 27.0  | 2322 | 0.1524          | 0.0879 | 0.0265 |
| 0.2259        | 28.0  | 2408 | 0.1566          | 0.0867 | 0.0264 |
| 0.2259        | 29.0  | 2494 | 0.1516          | 0.0842 | 0.0257 |
| 0.211         | 30.0  | 2580 | 0.1595          | 0.0891 | 0.0271 |
| 0.1963        | 31.0  | 2666 | 0.1500          | 0.0864 | 0.0260 |
| 0.2111        | 32.0  | 2752 | 0.1454          | 0.0857 | 0.0262 |
| 0.1849        | 33.0  | 2838 | 0.1473          | 0.0859 | 0.0264 |
| 0.1777        | 34.0  | 2924 | 0.1472          | 0.0862 | 0.0257 |
| 0.18          | 35.0  | 3010 | 0.1500          | 0.0859 | 0.0264 |
| 0.18          | 36.0  | 3096 | 0.1514          | 0.0842 | 0.0259 |
| 0.1762        | 37.0  | 3182 | 0.1509          | 0.0854 | 0.0256 |
| 0.1673        | 38.0  | 3268 | 0.1495          | 0.0847 | 0.0255 |
| 0.17          | 39.0  | 3354 | 0.1525          | 0.0813 | 0.0251 |
| 0.1616        | 40.0  | 3440 | 0.1484          | 0.0830 | 0.0251 |
| 0.1876        | 41.0  | 3526 | 0.1482          | 0.0813 | 0.0252 |
| 0.1627        | 42.0  | 3612 | 0.1459          | 0.0800 | 0.0248 |
| 0.1627        | 43.0  | 3698 | 0.1392          | 0.0798 | 0.0243 |
| 0.1875        | 44.0  | 3784 | 0.1415          | 0.0815 | 0.0245 |
| 0.1705        | 45.0  | 3870 | 0.1431          | 0.0774 | 0.0239 |
| 0.1565        | 46.0  | 3956 | 0.1404          | 0.0786 | 0.0240 |
| 0.1632        | 47.0  | 4042 | 0.1428          | 0.0769 | 0.0237 |
| 0.1577        | 48.0  | 4128 | 0.1439          | 0.0786 | 0.0237 |
| 0.1634        | 49.0  | 4214 | 0.1456          | 0.0800 | 0.0246 |
| 0.1574        | 50.0  | 4300 | 0.1409          | 0.0808 | 0.0242 |
| 0.1574        | 51.0  | 4386 | 0.1423          | 0.0796 | 0.0244 |
| 0.1468        | 52.0  | 4472 | 0.1453          | 0.0764 | 0.0234 |
| 0.1478        | 53.0  | 4558 | 0.1439          | 0.0813 | 0.0243 |
| 0.1456        | 54.0  | 4644 | 0.1400          | 0.0791 | 0.0244 |
| 0.1599        | 55.0  | 4730 | 0.1440          | 0.0820 | 0.0251 |
| 0.1435        | 56.0  | 4816 | 0.1469          | 0.0793 | 0.0241 |
| 0.1389        | 57.0  | 4902 | 0.1449          | 0.0813 | 0.0246 |
| 0.1389        | 58.0  | 4988 | 0.1447          | 0.0771 | 0.0244 |
| 0.1382        | 59.0  | 5074 | 0.1438          | 0.0798 | 0.0243 |
| 0.1393        | 60.0  | 5160 | 0.1440          | 0.0774 | 0.0239 |
| 0.1144        | 61.0  | 5246 | 0.1439          | 0.0791 | 0.0246 |
| 0.12          | 62.0  | 5332 | 0.1454          | 0.0788 | 0.0241 |
| 0.1285        | 63.0  | 5418 | 0.1461          | 0.0808 | 0.0247 |


### 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-06", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us