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# wav2vec2-large-xlsr-mec-ita-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: 0.1731
- Wer: 0.0951
- Cer: 0.0289

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.5899       | 1.0   | 86   | 3.2445          | 1.0    | 1.0    |
| 7.5695        | 2.0   | 172  | 2.9771          | 1.0    | 1.0    |
| 3.0711        | 3.0   | 258  | 2.9039          | 1.0    | 1.0    |
| 2.9235        | 4.0   | 344  | 2.8854          | 1.0    | 1.0    |
| 2.89          | 5.0   | 430  | 2.5992          | 1.0    | 1.0    |
| 2.3574        | 6.0   | 516  | 0.8211          | 0.3985 | 0.1061 |
| 1.0258        | 7.0   | 602  | 0.4657          | 0.2145 | 0.0602 |
| 1.0258        | 8.0   | 688  | 0.3749          | 0.1866 | 0.0522 |
| 0.7005        | 9.0   | 774  | 0.3151          | 0.1633 | 0.0465 |
| 0.5395        | 10.0  | 860  | 0.2897          | 0.1609 | 0.0446 |
| 0.455         | 11.0  | 946  | 0.2762          | 0.1466 | 0.0422 |
| 0.4392        | 12.0  | 1032 | 0.2520          | 0.1339 | 0.0385 |
| 0.3718        | 13.0  | 1118 | 0.2440          | 0.1213 | 0.0367 |
| 0.3695        | 14.0  | 1204 | 0.2308          | 0.1161 | 0.0351 |
| 0.3695        | 15.0  | 1290 | 0.2337          | 0.1063 | 0.0325 |
| 0.3303        | 16.0  | 1376 | 0.2242          | 0.1030 | 0.0326 |
| 0.2946        | 17.0  | 1462 | 0.2272          | 0.1094 | 0.0340 |
| 0.2853        | 18.0  | 1548 | 0.2115          | 0.1039 | 0.0326 |
| 0.2617        | 19.0  | 1634 | 0.2169          | 0.1068 | 0.0330 |
| 0.2765        | 20.0  | 1720 | 0.2141          | 0.1041 | 0.0319 |
| 0.2528        | 21.0  | 1806 | 0.2126          | 0.1006 | 0.0320 |
| 0.2528        | 22.0  | 1892 | 0.2047          | 0.1006 | 0.0317 |
| 0.2469        | 23.0  | 1978 | 0.1953          | 0.0984 | 0.0302 |
| 0.2325        | 24.0  | 2064 | 0.2028          | 0.1010 | 0.0310 |
| 0.2316        | 25.0  | 2150 | 0.2001          | 0.0977 | 0.0310 |
| 0.2274        | 26.0  | 2236 | 0.2024          | 0.0968 | 0.0305 |
| 0.2111        | 27.0  | 2322 | 0.2044          | 0.1015 | 0.0304 |
| 0.21          | 28.0  | 2408 | 0.1910          | 0.0946 | 0.0297 |
| 0.21          | 29.0  | 2494 | 0.1805          | 0.1013 | 0.0302 |
| 0.2069        | 30.0  | 2580 | 0.1852          | 0.0968 | 0.0301 |
| 0.1887        | 31.0  | 2666 | 0.1912          | 0.0941 | 0.0295 |
| 0.1928        | 32.0  | 2752 | 0.1929          | 0.0946 | 0.0299 |
| 0.1928        | 33.0  | 2838 | 0.1953          | 0.0929 | 0.0296 |
| 0.1806        | 34.0  | 2924 | 0.1866          | 0.0913 | 0.0284 |
| 0.1818        | 35.0  | 3010 | 0.1786          | 0.0927 | 0.0285 |
| 0.1818        | 36.0  | 3096 | 0.1770          | 0.0927 | 0.0289 |
| 0.1729        | 37.0  | 3182 | 0.1826          | 0.0915 | 0.0279 |
| 0.1768        | 38.0  | 3268 | 0.1785          | 0.0946 | 0.0281 |
| 0.1669        | 39.0  | 3354 | 0.1759          | 0.0946 | 0.0287 |
| 0.1774        | 40.0  | 3440 | 0.1731          | 0.0951 | 0.0289 |
| 0.1642        | 41.0  | 3526 | 0.1770          | 0.0937 | 0.0276 |
| 0.153         | 42.0  | 3612 | 0.1828          | 0.0937 | 0.0282 |
| 0.153         | 43.0  | 3698 | 0.1792          | 0.0949 | 0.0278 |
| 0.1541        | 44.0  | 3784 | 0.1834          | 0.0896 | 0.0273 |
| 0.1654        | 45.0  | 3870 | 0.1832          | 0.0927 | 0.0277 |
| 0.1632        | 46.0  | 3956 | 0.1849          | 0.0903 | 0.0266 |
| 0.154         | 47.0  | 4042 | 0.1773          | 0.0898 | 0.0268 |
| 0.1576        | 48.0  | 4128 | 0.1849          | 0.0901 | 0.0278 |
| 0.1381        | 49.0  | 4214 | 0.1797          | 0.0906 | 0.0269 |
| 0.151         | 50.0  | 4300 | 0.1811          | 0.0898 | 0.0270 |
| 0.151         | 51.0  | 4386 | 0.1827          | 0.0910 | 0.0272 |
| 0.1466        | 52.0  | 4472 | 0.1752          | 0.0915 | 0.0269 |
| 0.1563        | 53.0  | 4558 | 0.1893          | 0.0877 | 0.0268 |
| 0.1378        | 54.0  | 4644 | 0.1827          | 0.0865 | 0.0269 |
| 0.1313        | 55.0  | 4730 | 0.1737          | 0.0846 | 0.0266 |
| 0.148         | 56.0  | 4816 | 0.1786          | 0.0858 | 0.0269 |
| 0.1463        | 57.0  | 4902 | 0.1798          | 0.0863 | 0.0266 |
| 0.1463        | 58.0  | 4988 | 0.1819          | 0.0865 | 0.0266 |
| 0.1305        | 59.0  | 5074 | 0.1809          | 0.0870 | 0.0272 |
| 0.1326        | 60.0  | 5160 | 0.1847          | 0.0865 | 0.0271 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xlsr-mec-ita-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-mec-ita-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: 0.1731
* Wer: 0.0951
* Cer: 0.0289


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 4.28.1
* Pytorch 2.0.0+cu118
* 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 4.28.1
* Pytorch 2.0.0+cu118
* 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 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3