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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-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: 0.1723
- Wer: 0.1003
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.9102       | 1.0   | 86   | 8.9936          | 0.9998 | 0.9850 |
| 12.3774       | 2.0   | 172  | 4.2002          | 1.0    | 0.9765 |
| 6.1033        | 3.0   | 258  | 2.9777          | 1.0    | 1.0    |
| 3.0498        | 4.0   | 344  | 2.9197          | 1.0    | 1.0    |
| 2.9326        | 5.0   | 430  | 2.9070          | 1.0    | 1.0    |
| 2.9013        | 6.0   | 516  | 2.9092          | 1.0    | 1.0    |
| 2.8884        | 7.0   | 602  | 2.8986          | 1.0    | 1.0    |
| 2.8884        | 8.0   | 688  | 2.7090          | 1.0    | 0.9999 |
| 2.846         | 9.0   | 774  | 1.6263          | 1.0    | 0.5386 |
| 2.2318        | 10.0  | 860  | 0.5529          | 0.2735 | 0.0770 |
| 1.0214        | 11.0  | 946  | 0.3765          | 0.1925 | 0.0586 |
| 0.6611        | 12.0  | 1032 | 0.3123          | 0.1703 | 0.0514 |
| 0.4931        | 13.0  | 1118 | 0.2772          | 0.1523 | 0.0467 |
| 0.4232        | 14.0  | 1204 | 0.2599          | 0.1284 | 0.0426 |
| 0.4232        | 15.0  | 1290 | 0.2462          | 0.1216 | 0.0413 |
| 0.375         | 16.0  | 1376 | 0.2336          | 0.1178 | 0.0410 |
| 0.3507        | 17.0  | 1462 | 0.2269          | 0.1147 | 0.0406 |
| 0.3264        | 18.0  | 1548 | 0.2186          | 0.1137 | 0.0394 |
| 0.3115        | 19.0  | 1634 | 0.2166          | 0.1106 | 0.0386 |
| 0.2841        | 20.0  | 1720 | 0.2069          | 0.1087 | 0.0379 |
| 0.2786        | 21.0  | 1806 | 0.2035          | 0.1073 | 0.0381 |
| 0.2786        | 22.0  | 1892 | 0.2042          | 0.1097 | 0.0374 |
| 0.2382        | 23.0  | 1978 | 0.1986          | 0.1051 | 0.0364 |
| 0.2406        | 24.0  | 2064 | 0.1943          | 0.1066 | 0.0368 |
| 0.2573        | 25.0  | 2150 | 0.1902          | 0.1008 | 0.0359 |
| 0.2336        | 26.0  | 2236 | 0.1896          | 0.1030 | 0.0360 |
| 0.2089        | 27.0  | 2322 | 0.1958          | 0.1063 | 0.0368 |
| 0.2173        | 28.0  | 2408 | 0.1922          | 0.1070 | 0.0370 |
| 0.2173        | 29.0  | 2494 | 0.1913          | 0.1042 | 0.0366 |
| 0.2147        | 30.0  | 2580 | 0.1885          | 0.1006 | 0.0357 |
| 0.2087        | 31.0  | 2666 | 0.1850          | 0.1044 | 0.0359 |
| 0.1838        | 32.0  | 2752 | 0.1855          | 0.1054 | 0.0365 |
| 0.1863        | 33.0  | 2838 | 0.1805          | 0.1003 | 0.0355 |
| 0.1945        | 34.0  | 2924 | 0.1846          | 0.1003 | 0.0351 |
| 0.1774        | 35.0  | 3010 | 0.1814          | 0.1003 | 0.0353 |
| 0.1774        | 36.0  | 3096 | 0.1803          | 0.0984 | 0.0344 |
| 0.1887        | 37.0  | 3182 | 0.1752          | 0.1006 | 0.0344 |
| 0.164         | 38.0  | 3268 | 0.1812          | 0.1006 | 0.0347 |
| 0.1829        | 39.0  | 3354 | 0.1777          | 0.0989 | 0.0342 |
| 0.1838        | 40.0  | 3440 | 0.1793          | 0.1015 | 0.0349 |
| 0.1574        | 41.0  | 3526 | 0.1773          | 0.1006 | 0.0347 |
| 0.1597        | 42.0  | 3612 | 0.1723          | 0.1003 | 0.0337 |
| 0.1597        | 43.0  | 3698 | 0.1757          | 0.0989 | 0.0343 |
| 0.1548        | 44.0  | 3784 | 0.1727          | 0.1006 | 0.0352 |
| 0.1651        | 45.0  | 3870 | 0.1789          | 0.0994 | 0.0345 |
| 0.1604        | 46.0  | 3956 | 0.1762          | 0.0989 | 0.0334 |
| 0.1366        | 47.0  | 4042 | 0.1759          | 0.0953 | 0.0327 |
| 0.153         | 48.0  | 4128 | 0.1762          | 0.0982 | 0.0341 |
| 0.1608        | 49.0  | 4214 | 0.1803          | 0.0972 | 0.0344 |
| 0.1429        | 50.0  | 4300 | 0.1772          | 0.0965 | 0.0342 |
| 0.1429        | 51.0  | 4386 | 0.1802          | 0.0989 | 0.0345 |
| 0.1382        | 52.0  | 4472 | 0.1788          | 0.0963 | 0.0341 |
| 0.1408        | 53.0  | 4558 | 0.1785          | 0.0960 | 0.0342 |
| 0.1267        | 54.0  | 4644 | 0.1789          | 0.0979 | 0.0342 |
| 0.1531        | 55.0  | 4730 | 0.1786          | 0.0960 | 0.0336 |
| 0.1357        | 56.0  | 4816 | 0.1784          | 0.0943 | 0.0335 |
| 0.146         | 57.0  | 4902 | 0.1811          | 0.0958 | 0.0337 |
| 0.146         | 58.0  | 4988 | 0.1813          | 0.0951 | 0.0338 |
| 0.1363        | 59.0  | 5074 | 0.1813          | 0.0977 | 0.0340 |
| 0.1366        | 60.0  | 5160 | 0.1785          | 0.0991 | 0.0345 |
| 0.1502        | 61.0  | 5246 | 0.1789          | 0.0936 | 0.0333 |
| 0.1261        | 62.0  | 5332 | 0.1771          | 0.0984 | 0.0339 |


### 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-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-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: 0.1723
* Wer: 0.1003
* 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



### 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