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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-clean-04

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: 0.1664
- Wer: 0.0944
- Cer: 0.0281

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 21.1889       | 1.0   | 67   | 3.3270          | 1.0    | 1.0    |
| 7.4773        | 2.0   | 134  | 2.9699          | 1.0    | 1.0    |
| 3.0098        | 3.0   | 201  | 2.9123          | 1.0    | 1.0    |
| 3.0098        | 4.0   | 268  | 2.9135          | 1.0    | 1.0    |
| 2.9096        | 5.0   | 335  | 2.8647          | 1.0    | 1.0    |
| 2.8469        | 6.0   | 402  | 2.4765          | 1.0    | 0.9998 |
| 2.8469        | 7.0   | 469  | 0.8785          | 0.4283 | 0.1059 |
| 1.7225        | 8.0   | 536  | 0.4984          | 0.2262 | 0.0588 |
| 0.8041        | 9.0   | 603  | 0.3737          | 0.1973 | 0.0517 |
| 0.8041        | 10.0  | 670  | 0.3288          | 0.1816 | 0.0496 |
| 0.5862        | 11.0  | 737  | 0.3055          | 0.1751 | 0.0474 |
| 0.4768        | 12.0  | 804  | 0.2713          | 0.1492 | 0.0411 |
| 0.4768        | 13.0  | 871  | 0.2496          | 0.1394 | 0.0393 |
| 0.4019        | 14.0  | 938  | 0.2453          | 0.1319 | 0.0380 |
| 0.3483        | 15.0  | 1005 | 0.2310          | 0.1203 | 0.0353 |
| 0.3483        | 16.0  | 1072 | 0.2185          | 0.1196 | 0.0347 |
| 0.3276        | 17.0  | 1139 | 0.2147          | 0.1152 | 0.0345 |
| 0.2945        | 18.0  | 1206 | 0.2067          | 0.1090 | 0.0324 |
| 0.2945        | 19.0  | 1273 | 0.1995          | 0.1066 | 0.0327 |
| 0.3026        | 20.0  | 1340 | 0.2011          | 0.1019 | 0.0322 |
| 0.2541        | 21.0  | 1407 | 0.1959          | 0.1022 | 0.0316 |
| 0.2541        | 22.0  | 1474 | 0.1960          | 0.1046 | 0.0318 |
| 0.2472        | 23.0  | 1541 | 0.1890          | 0.1056 | 0.0321 |
| 0.2374        | 24.0  | 1608 | 0.1882          | 0.0971 | 0.0311 |
| 0.2374        | 25.0  | 1675 | 0.1843          | 0.0961 | 0.0300 |
| 0.2217        | 26.0  | 1742 | 0.1837          | 0.1032 | 0.0311 |
| 0.2352        | 27.0  | 1809 | 0.1845          | 0.0971 | 0.0304 |
| 0.2352        | 28.0  | 1876 | 0.1809          | 0.0985 | 0.0303 |
| 0.2207        | 29.0  | 1943 | 0.1761          | 0.0937 | 0.0297 |
| 0.2067        | 30.0  | 2010 | 0.1791          | 0.0961 | 0.0294 |
| 0.2067        | 31.0  | 2077 | 0.1764          | 0.0978 | 0.0299 |
| 0.1956        | 32.0  | 2144 | 0.1762          | 0.1019 | 0.0303 |
| 0.1981        | 33.0  | 2211 | 0.1809          | 0.0964 | 0.0299 |
| 0.1981        | 34.0  | 2278 | 0.1828          | 0.0944 | 0.0298 |
| 0.1741        | 35.0  | 2345 | 0.1799          | 0.0930 | 0.0293 |
| 0.1776        | 36.0  | 2412 | 0.1748          | 0.0930 | 0.0289 |
| 0.1776        | 37.0  | 2479 | 0.1767          | 0.0927 | 0.0292 |
| 0.184         | 38.0  | 2546 | 0.1755          | 0.0882 | 0.0286 |
| 0.1887        | 39.0  | 2613 | 0.1753          | 0.0927 | 0.0292 |
| 0.1887        | 40.0  | 2680 | 0.1698          | 0.0923 | 0.0281 |
| 0.1687        | 41.0  | 2747 | 0.1773          | 0.0927 | 0.0288 |
| 0.1669        | 42.0  | 2814 | 0.1760          | 0.0957 | 0.0291 |
| 0.1669        | 43.0  | 2881 | 0.1770          | 0.0920 | 0.0288 |
| 0.143         | 44.0  | 2948 | 0.1734          | 0.0896 | 0.0283 |
| 0.1555        | 45.0  | 3015 | 0.1748          | 0.0903 | 0.0283 |
| 0.1555        | 46.0  | 3082 | 0.1756          | 0.0937 | 0.0289 |
| 0.1543        | 47.0  | 3149 | 0.1714          | 0.0917 | 0.0281 |
| 0.145         | 48.0  | 3216 | 0.1677          | 0.0927 | 0.0284 |
| 0.145         | 49.0  | 3283 | 0.1698          | 0.0937 | 0.0287 |
| 0.1451        | 50.0  | 3350 | 0.1709          | 0.0927 | 0.0290 |
| 0.1422        | 51.0  | 3417 | 0.1674          | 0.0930 | 0.0286 |
| 0.1422        | 52.0  | 3484 | 0.1680          | 0.0930 | 0.0281 |
| 0.1466        | 53.0  | 3551 | 0.1664          | 0.0944 | 0.0281 |
| 0.1371        | 54.0  | 3618 | 0.1749          | 0.0920 | 0.0282 |
| 0.1371        | 55.0  | 3685 | 0.1761          | 0.0934 | 0.0285 |
| 0.1334        | 56.0  | 3752 | 0.1727          | 0.0903 | 0.0280 |
| 0.1365        | 57.0  | 3819 | 0.1739          | 0.0923 | 0.0284 |
| 0.1365        | 58.0  | 3886 | 0.1754          | 0.0920 | 0.0279 |
| 0.1328        | 59.0  | 3953 | 0.1748          | 0.0920 | 0.0285 |
| 0.1378        | 60.0  | 4020 | 0.1790          | 0.0903 | 0.0280 |
| 0.1378        | 61.0  | 4087 | 0.1739          | 0.0927 | 0.0280 |
| 0.1417        | 62.0  | 4154 | 0.1722          | 0.0917 | 0.0283 |
| 0.13          | 63.0  | 4221 | 0.1718          | 0.0913 | 0.0285 |
| 0.13          | 64.0  | 4288 | 0.1796          | 0.0940 | 0.0287 |
| 0.131         | 65.0  | 4355 | 0.1765          | 0.0920 | 0.0289 |
| 0.131         | 66.0  | 4422 | 0.1740          | 0.0913 | 0.0288 |
| 0.131         | 67.0  | 4489 | 0.1760          | 0.0968 | 0.0296 |
| 0.1311        | 68.0  | 4556 | 0.1757          | 0.0913 | 0.0284 |
| 0.1354        | 69.0  | 4623 | 0.1754          | 0.0920 | 0.0286 |
| 0.1354        | 70.0  | 4690 | 0.1757          | 0.0920 | 0.0285 |
| 0.1303        | 71.0  | 4757 | 0.1739          | 0.0882 | 0.0281 |
| 0.1252        | 72.0  | 4824 | 0.1735          | 0.0893 | 0.0281 |
| 0.1252        | 73.0  | 4891 | 0.1728          | 0.0913 | 0.0285 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+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-04", "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-04
========================================================


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: 0.1664
* Wer: 0.0944
* Cer: 0.0281


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 2.0.0+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 2.0.0+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 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3