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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-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: 0.1868
- Wer: 0.0906
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.5317       | 1.0   | 86   | 3.4264          | 1.0    | 1.0    |
| 8.6384        | 2.0   | 172  | 3.0049          | 1.0    | 1.0    |
| 3.0821        | 3.0   | 258  | 2.9416          | 1.0    | 1.0    |
| 2.9357        | 4.0   | 344  | 2.9331          | 1.0    | 1.0    |
| 2.9035        | 5.0   | 430  | 2.9165          | 1.0    | 1.0    |
| 2.8816        | 6.0   | 516  | 2.6902          | 1.0    | 1.0    |
| 2.3317        | 7.0   | 602  | 1.0713          | 0.7650 | 0.1968 |
| 2.3317        | 8.0   | 688  | 0.5039          | 0.2577 | 0.0686 |
| 1.0095        | 9.0   | 774  | 0.3925          | 0.2034 | 0.0550 |
| 0.6723        | 10.0  | 860  | 0.3236          | 0.1740 | 0.0477 |
| 0.5441        | 11.0  | 946  | 0.3129          | 0.1486 | 0.0430 |
| 0.4353        | 12.0  | 1032 | 0.2682          | 0.1429 | 0.0414 |
| 0.391         | 13.0  | 1118 | 0.2518          | 0.1316 | 0.0384 |
| 0.3714        | 14.0  | 1204 | 0.2512          | 0.1244 | 0.0363 |
| 0.3714        | 15.0  | 1290 | 0.2382          | 0.1197 | 0.0356 |
| 0.3316        | 16.0  | 1376 | 0.2245          | 0.1155 | 0.0351 |
| 0.3111        | 17.0  | 1462 | 0.2191          | 0.1089 | 0.0332 |
| 0.2925        | 18.0  | 1548 | 0.2103          | 0.1044 | 0.0317 |
| 0.2865        | 19.0  | 1634 | 0.2053          | 0.1061 | 0.0324 |
| 0.2679        | 20.0  | 1720 | 0.2100          | 0.1002 | 0.0323 |
| 0.2429        | 21.0  | 1806 | 0.1974          | 0.0995 | 0.0312 |
| 0.2429        | 22.0  | 1892 | 0.2043          | 0.0975 | 0.0307 |
| 0.2421        | 23.0  | 1978 | 0.2041          | 0.0973 | 0.0306 |
| 0.2366        | 24.0  | 2064 | 0.2022          | 0.0965 | 0.0300 |
| 0.2262        | 25.0  | 2150 | 0.1995          | 0.0990 | 0.0306 |
| 0.2084        | 26.0  | 2236 | 0.1954          | 0.0992 | 0.0306 |
| 0.2204        | 27.0  | 2322 | 0.1966          | 0.0987 | 0.0298 |
| 0.2151        | 28.0  | 2408 | 0.1983          | 0.0965 | 0.0297 |
| 0.2151        | 29.0  | 2494 | 0.1970          | 0.0913 | 0.0285 |
| 0.1998        | 30.0  | 2580 | 0.1980          | 0.0938 | 0.0285 |
| 0.1944        | 31.0  | 2666 | 0.1871          | 0.0943 | 0.0289 |
| 0.1929        | 32.0  | 2752 | 0.2006          | 0.0926 | 0.0281 |
| 0.2138        | 33.0  | 2838 | 0.1925          | 0.0913 | 0.0286 |
| 0.1913        | 34.0  | 2924 | 0.1921          | 0.0916 | 0.0285 |
| 0.1842        | 35.0  | 3010 | 0.1949          | 0.0913 | 0.0284 |
| 0.1842        | 36.0  | 3096 | 0.1938          | 0.0938 | 0.0294 |
| 0.1906        | 37.0  | 3182 | 0.1944          | 0.0938 | 0.0295 |
| 0.182         | 38.0  | 3268 | 0.1920          | 0.0889 | 0.0284 |
| 0.1729        | 39.0  | 3354 | 0.1932          | 0.0911 | 0.0290 |
| 0.1766        | 40.0  | 3440 | 0.1868          | 0.0906 | 0.0281 |
| 0.1789        | 41.0  | 3526 | 0.1914          | 0.0903 | 0.0282 |
| 0.1595        | 42.0  | 3612 | 0.1871          | 0.0894 | 0.0280 |
| 0.1595        | 43.0  | 3698 | 0.1954          | 0.0886 | 0.0274 |
| 0.1632        | 44.0  | 3784 | 0.1868          | 0.0901 | 0.0280 |
| 0.1686        | 45.0  | 3870 | 0.2000          | 0.0866 | 0.0271 |
| 0.1577        | 46.0  | 3956 | 0.1891          | 0.0884 | 0.0276 |
| 0.1572        | 47.0  | 4042 | 0.1941          | 0.0886 | 0.0277 |
| 0.1581        | 48.0  | 4128 | 0.1949          | 0.0876 | 0.0270 |
| 0.154         | 49.0  | 4214 | 0.1942          | 0.0899 | 0.0279 |
| 0.1519        | 50.0  | 4300 | 0.1938          | 0.0886 | 0.0272 |
| 0.1519        | 51.0  | 4386 | 0.1979          | 0.0908 | 0.0286 |
| 0.1494        | 52.0  | 4472 | 0.2006          | 0.0889 | 0.0277 |
| 0.1516        | 53.0  | 4558 | 0.2010          | 0.0906 | 0.0287 |
| 0.1353        | 54.0  | 4644 | 0.2045          | 0.0901 | 0.0286 |
| 0.1473        | 55.0  | 4730 | 0.1949          | 0.0899 | 0.0282 |
| 0.1417        | 56.0  | 4816 | 0.1923          | 0.0906 | 0.0289 |
| 0.1398        | 57.0  | 4902 | 0.1923          | 0.0906 | 0.0283 |
| 0.1398        | 58.0  | 4988 | 0.1960          | 0.0894 | 0.0279 |
| 0.1449        | 59.0  | 5074 | 0.1964          | 0.0913 | 0.0283 |
| 0.1412        | 60.0  | 5160 | 0.1998          | 0.0899 | 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-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-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: 0.1868
* Wer: 0.0906
* 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 2.0.1+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