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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-clean-10

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: 0.1658
- Wer: 0.0947
- Cer: 0.0291

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 21.131        | 1.0   | 67   | 3.3444          | 1.0    | 1.0    |
| 7.1783        | 2.0   | 134  | 2.9805          | 1.0    | 1.0    |
| 3.0142        | 3.0   | 201  | 2.9060          | 1.0    | 1.0    |
| 3.0142        | 4.0   | 268  | 2.8839          | 1.0    | 1.0    |
| 2.9114        | 5.0   | 335  | 2.8077          | 1.0    | 1.0    |
| 2.7413        | 6.0   | 402  | 1.8757          | 1.0    | 0.5239 |
| 2.7413        | 7.0   | 469  | 0.6953          | 0.3608 | 0.0901 |
| 1.3808        | 8.0   | 536  | 0.4579          | 0.2221 | 0.0576 |
| 0.7472        | 9.0   | 603  | 0.3593          | 0.2    | 0.0523 |
| 0.7472        | 10.0  | 670  | 0.3176          | 0.1816 | 0.0485 |
| 0.564         | 11.0  | 737  | 0.2996          | 0.1680 | 0.0467 |
| 0.47          | 12.0  | 804  | 0.2680          | 0.1564 | 0.0427 |
| 0.47          | 13.0  | 871  | 0.2549          | 0.1455 | 0.0397 |
| 0.3958        | 14.0  | 938  | 0.2384          | 0.1322 | 0.0371 |
| 0.346         | 15.0  | 1005 | 0.2362          | 0.1233 | 0.0361 |
| 0.346         | 16.0  | 1072 | 0.2118          | 0.1145 | 0.0338 |
| 0.3286        | 17.0  | 1139 | 0.2110          | 0.1141 | 0.0336 |
| 0.2927        | 18.0  | 1206 | 0.2048          | 0.1114 | 0.0329 |
| 0.2927        | 19.0  | 1273 | 0.1992          | 0.1022 | 0.0316 |
| 0.2996        | 20.0  | 1340 | 0.2000          | 0.1039 | 0.0317 |
| 0.2532        | 21.0  | 1407 | 0.1981          | 0.1015 | 0.0311 |
| 0.2532        | 22.0  | 1474 | 0.1961          | 0.1046 | 0.0311 |
| 0.2465        | 23.0  | 1541 | 0.1902          | 0.1073 | 0.0314 |
| 0.2369        | 24.0  | 1608 | 0.1871          | 0.0957 | 0.0302 |
| 0.2369        | 25.0  | 1675 | 0.1850          | 0.0964 | 0.0299 |
| 0.2224        | 26.0  | 1742 | 0.1817          | 0.0985 | 0.0298 |
| 0.2352        | 27.0  | 1809 | 0.1824          | 0.0971 | 0.0304 |
| 0.2352        | 28.0  | 1876 | 0.1859          | 0.0947 | 0.0303 |
| 0.2191        | 29.0  | 1943 | 0.1822          | 0.0923 | 0.0300 |
| 0.2064        | 30.0  | 2010 | 0.1773          | 0.0934 | 0.0297 |
| 0.2064        | 31.0  | 2077 | 0.1794          | 0.0947 | 0.0293 |
| 0.1964        | 32.0  | 2144 | 0.1763          | 0.0934 | 0.0296 |
| 0.1962        | 33.0  | 2211 | 0.1748          | 0.0927 | 0.0301 |
| 0.1962        | 34.0  | 2278 | 0.1789          | 0.0954 | 0.0296 |
| 0.1766        | 35.0  | 2345 | 0.1729          | 0.0930 | 0.0285 |
| 0.1782        | 36.0  | 2412 | 0.1738          | 0.0913 | 0.0285 |
| 0.1782        | 37.0  | 2479 | 0.1714          | 0.0957 | 0.0293 |
| 0.1835        | 38.0  | 2546 | 0.1739          | 0.0947 | 0.0296 |
| 0.1907        | 39.0  | 2613 | 0.1725          | 0.0913 | 0.0290 |
| 0.1907        | 40.0  | 2680 | 0.1718          | 0.0937 | 0.0294 |
| 0.1667        | 41.0  | 2747 | 0.1718          | 0.0954 | 0.0297 |
| 0.169         | 42.0  | 2814 | 0.1753          | 0.0927 | 0.0292 |
| 0.169         | 43.0  | 2881 | 0.1737          | 0.0947 | 0.0295 |
| 0.1425        | 44.0  | 2948 | 0.1684          | 0.0940 | 0.0292 |
| 0.1541        | 45.0  | 3015 | 0.1751          | 0.0940 | 0.0293 |
| 0.1541        | 46.0  | 3082 | 0.1735          | 0.0913 | 0.0286 |
| 0.1539        | 47.0  | 3149 | 0.1749          | 0.0961 | 0.0292 |
| 0.1456        | 48.0  | 3216 | 0.1703          | 0.0930 | 0.0290 |
| 0.1456        | 49.0  | 3283 | 0.1705          | 0.0906 | 0.0285 |
| 0.1449        | 50.0  | 3350 | 0.1702          | 0.0940 | 0.0289 |
| 0.1418        | 51.0  | 3417 | 0.1675          | 0.0903 | 0.0280 |
| 0.1418        | 52.0  | 3484 | 0.1708          | 0.0910 | 0.0285 |
| 0.1428        | 53.0  | 3551 | 0.1658          | 0.0947 | 0.0291 |
| 0.1388        | 54.0  | 3618 | 0.1715          | 0.0927 | 0.0287 |
| 0.1388        | 55.0  | 3685 | 0.1692          | 0.0889 | 0.0278 |
| 0.1321        | 56.0  | 3752 | 0.1695          | 0.0882 | 0.0275 |
| 0.135         | 57.0  | 3819 | 0.1715          | 0.0940 | 0.0283 |
| 0.135         | 58.0  | 3886 | 0.1676          | 0.0903 | 0.0278 |
| 0.1335        | 59.0  | 3953 | 0.1687          | 0.0930 | 0.0282 |
| 0.1378        | 60.0  | 4020 | 0.1743          | 0.0923 | 0.0286 |
| 0.1378        | 61.0  | 4087 | 0.1664          | 0.0920 | 0.0276 |
| 0.142         | 62.0  | 4154 | 0.1679          | 0.0910 | 0.0274 |
| 0.1299        | 63.0  | 4221 | 0.1702          | 0.0913 | 0.0278 |
| 0.1299        | 64.0  | 4288 | 0.1705          | 0.0937 | 0.0283 |
| 0.1303        | 65.0  | 4355 | 0.1710          | 0.0913 | 0.0281 |
| 0.1305        | 66.0  | 4422 | 0.1672          | 0.0927 | 0.0280 |
| 0.1305        | 67.0  | 4489 | 0.1664          | 0.0974 | 0.0291 |
| 0.1312        | 68.0  | 4556 | 0.1659          | 0.0985 | 0.0287 |
| 0.1335        | 69.0  | 4623 | 0.1664          | 0.0910 | 0.0275 |
| 0.1335        | 70.0  | 4690 | 0.1680          | 0.0964 | 0.0286 |
| 0.1298        | 71.0  | 4757 | 0.1714          | 0.0951 | 0.0285 |
| 0.1245        | 72.0  | 4824 | 0.1713          | 0.0906 | 0.0275 |
| 0.1245        | 73.0  | 4891 | 0.1692          | 0.0927 | 0.0280 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xlsr-mecita-coraa-portuguese-all-clean-10", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xlsr-mecita-coraa-portuguese-all-clean-10
========================================================


This model is a fine-tuned version of Edresson/wav2vec2-large-xlsr-coraa-portuguese on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1658
* Wer: 0.0947
* Cer: 0.0291


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



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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 ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3