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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-01

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: 0.1409
- Wer: 0.0881
- Cer: 0.0252

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 31.6902       | 1.0   | 86   | 3.2464          | 1.0    | 1.0    |
| 7.8893        | 2.0   | 172  | 3.0260          | 1.0    | 1.0    |
| 3.0632        | 3.0   | 258  | 2.9107          | 1.0    | 1.0    |
| 2.9359        | 4.0   | 344  | 2.9192          | 1.0    | 1.0    |
| 2.8959        | 5.0   | 430  | 2.6958          | 1.0    | 1.0    |
| 2.4935        | 6.0   | 516  | 0.9688          | 0.7493 | 0.1726 |
| 1.1534        | 7.0   | 602  | 0.4912          | 0.2384 | 0.0645 |
| 1.1534        | 8.0   | 688  | 0.3807          | 0.1956 | 0.0539 |
| 0.7254        | 9.0   | 774  | 0.3121          | 0.1735 | 0.0471 |
| 0.5771        | 10.0  | 860  | 0.2682          | 0.1609 | 0.0437 |
| 0.4772        | 11.0  | 946  | 0.2458          | 0.1555 | 0.0418 |
| 0.4056        | 12.0  | 1032 | 0.2293          | 0.1405 | 0.0381 |
| 0.3781        | 13.0  | 1118 | 0.2294          | 0.1336 | 0.0376 |
| 0.3607        | 14.0  | 1204 | 0.2177          | 0.1228 | 0.0350 |
| 0.3607        | 15.0  | 1290 | 0.2010          | 0.1159 | 0.0328 |
| 0.3061        | 16.0  | 1376 | 0.1963          | 0.1134 | 0.0329 |
| 0.3163        | 17.0  | 1462 | 0.1901          | 0.1166 | 0.0323 |
| 0.3313        | 18.0  | 1548 | 0.1837          | 0.1102 | 0.0312 |
| 0.2752        | 19.0  | 1634 | 0.1742          | 0.1078 | 0.0306 |
| 0.2819        | 20.0  | 1720 | 0.1742          | 0.1019 | 0.0293 |
| 0.2445        | 21.0  | 1806 | 0.1705          | 0.1083 | 0.0304 |
| 0.2445        | 22.0  | 1892 | 0.1700          | 0.1026 | 0.0297 |
| 0.2384        | 23.0  | 1978 | 0.1676          | 0.1038 | 0.0294 |
| 0.2468        | 24.0  | 2064 | 0.1627          | 0.1014 | 0.0285 |
| 0.2409        | 25.0  | 2150 | 0.1625          | 0.1011 | 0.0283 |
| 0.236         | 26.0  | 2236 | 0.1605          | 0.0992 | 0.0278 |
| 0.2264        | 27.0  | 2322 | 0.1587          | 0.0977 | 0.0281 |
| 0.2326        | 28.0  | 2408 | 0.1583          | 0.0982 | 0.0280 |
| 0.2326        | 29.0  | 2494 | 0.1592          | 0.0972 | 0.0277 |
| 0.2206        | 30.0  | 2580 | 0.1595          | 0.0987 | 0.0285 |
| 0.2035        | 31.0  | 2666 | 0.1536          | 0.0974 | 0.0276 |
| 0.2156        | 32.0  | 2752 | 0.1544          | 0.0950 | 0.0272 |
| 0.1936        | 33.0  | 2838 | 0.1558          | 0.0945 | 0.0266 |
| 0.1846        | 34.0  | 2924 | 0.1551          | 0.0923 | 0.0262 |
| 0.1865        | 35.0  | 3010 | 0.1535          | 0.0972 | 0.0275 |
| 0.1865        | 36.0  | 3096 | 0.1513          | 0.0979 | 0.0280 |
| 0.1807        | 37.0  | 3182 | 0.1517          | 0.0925 | 0.0268 |
| 0.1745        | 38.0  | 3268 | 0.1496          | 0.0955 | 0.0271 |
| 0.1745        | 39.0  | 3354 | 0.1490          | 0.0952 | 0.0261 |
| 0.1664        | 40.0  | 3440 | 0.1465          | 0.0955 | 0.0268 |
| 0.192         | 41.0  | 3526 | 0.1486          | 0.0965 | 0.0273 |
| 0.1683        | 42.0  | 3612 | 0.1452          | 0.0928 | 0.0266 |
| 0.1683        | 43.0  | 3698 | 0.1458          | 0.0906 | 0.0257 |
| 0.1906        | 44.0  | 3784 | 0.1515          | 0.0920 | 0.0272 |
| 0.1749        | 45.0  | 3870 | 0.1479          | 0.0935 | 0.0271 |
| 0.1563        | 46.0  | 3956 | 0.1477          | 0.0908 | 0.0262 |
| 0.1637        | 47.0  | 4042 | 0.1477          | 0.0930 | 0.0267 |
| 0.1618        | 48.0  | 4128 | 0.1409          | 0.0881 | 0.0252 |
| 0.1636        | 49.0  | 4214 | 0.1438          | 0.0938 | 0.0257 |
| 0.1624        | 50.0  | 4300 | 0.1434          | 0.0898 | 0.0252 |
| 0.1624        | 51.0  | 4386 | 0.1474          | 0.0920 | 0.0257 |
| 0.15          | 52.0  | 4472 | 0.1466          | 0.0883 | 0.0252 |
| 0.1518        | 53.0  | 4558 | 0.1524          | 0.0955 | 0.0265 |
| 0.1486        | 54.0  | 4644 | 0.1468          | 0.0896 | 0.0252 |
| 0.1614        | 55.0  | 4730 | 0.1430          | 0.0906 | 0.0253 |
| 0.1475        | 56.0  | 4816 | 0.1451          | 0.0898 | 0.0257 |
| 0.1421        | 57.0  | 4902 | 0.1432          | 0.0906 | 0.0259 |
| 0.1421        | 58.0  | 4988 | 0.1435          | 0.0881 | 0.0258 |
| 0.1419        | 59.0  | 5074 | 0.1462          | 0.0901 | 0.0259 |
| 0.1433        | 60.0  | 5160 | 0.1432          | 0.0886 | 0.0253 |
| 0.1177        | 61.0  | 5246 | 0.1467          | 0.0871 | 0.0250 |
| 0.1249        | 62.0  | 5332 | 0.1498          | 0.0888 | 0.0257 |
| 0.1332        | 63.0  | 5418 | 0.1493          | 0.0898 | 0.0260 |
| 0.142         | 64.0  | 5504 | 0.1464          | 0.0906 | 0.0258 |
| 0.142         | 65.0  | 5590 | 0.1434          | 0.0906 | 0.0256 |
| 0.1441        | 66.0  | 5676 | 0.1465          | 0.0923 | 0.0261 |
| 0.1252        | 67.0  | 5762 | 0.1449          | 0.0906 | 0.0256 |
| 0.1282        | 68.0  | 5848 | 0.1461          | 0.0896 | 0.0257 |


### 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-01", "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-01
==================================================


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: 0.1409
* Wer: 0.0881
* Cer: 0.0252


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