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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-07

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: 0.1508
- Wer: 0.1043
- Cer: 0.0313

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 29.285        | 1.0   | 86   | 4.4517          | 1.0    | 1.0    |
| 9.6798        | 2.0   | 172  | 3.2787          | 0.9687 | 0.9478 |
| 4.4299        | 3.0   | 258  | 3.1545          | 0.9755 | 0.9807 |
| 4.1881        | 4.0   | 344  | 2.9177          | 1.0    | 1.0    |
| 4.2218        | 5.0   | 430  | 2.9044          | 1.0    | 1.0    |
| 3.3289        | 6.0   | 516  | 2.9194          | 0.9679 | 0.9709 |
| 4.2916        | 7.0   | 602  | 2.8598          | 0.9563 | 0.9188 |
| 4.2916        | 8.0   | 688  | 2.9310          | 0.9691 | 0.9357 |
| 3.9718        | 9.0   | 774  | 2.8625          | 0.9589 | 0.9022 |
| 3.7729        | 10.0  | 860  | 2.7969          | 0.9597 | 0.8810 |
| 3.9658        | 11.0  | 946  | 2.8245          | 0.9623 | 0.8708 |
| 3.9463        | 12.0  | 1032 | 2.7623          | 0.9813 | 0.8284 |
| 3.7464        | 13.0  | 1118 | 2.7775          | 0.9687 | 0.8157 |
| 3.4367        | 14.0  | 1204 | 2.7377          | 0.9827 | 0.7907 |
| 3.4367        | 15.0  | 1290 | 2.7610          | 0.9762 | 0.7866 |
| 3.7793        | 16.0  | 1376 | 2.7348          | 0.9779 | 0.7686 |
| 3.5917        | 17.0  | 1462 | 2.7264          | 0.9772 | 0.7630 |
| 3.6592        | 18.0  | 1548 | 2.8368          | 0.9682 | 0.7726 |
| 3.6796        | 19.0  | 1634 | 2.6872          | 0.9691 | 0.7746 |
| 3.6374        | 20.0  | 1720 | 2.6675          | 0.9832 | 0.7497 |
| 3.5981        | 21.0  | 1806 | 2.6653          | 0.9813 | 0.7553 |
| 3.5981        | 22.0  | 1892 | 2.6524          | 0.9631 | 0.7620 |
| 3.3592        | 23.0  | 1978 | 2.6218          | 0.9764 | 0.7477 |
| 3.3905        | 24.0  | 2064 | 2.6224          | 0.9759 | 0.7319 |
| 3.7128        | 25.0  | 2150 | 2.5871          | 0.9747 | 0.7238 |
| 3.1975        | 26.0  | 2236 | 2.5861          | 0.9679 | 0.7138 |
| 3.1143        | 27.0  | 2322 | 2.6368          | 0.9623 | 0.7400 |
| 3.3341        | 28.0  | 2408 | 2.5720          | 0.9643 | 0.7422 |
| 3.3341        | 29.0  | 2494 | 2.5195          | 0.9572 | 0.7281 |
| 3.1484        | 30.0  | 2580 | 2.4978          | 0.9604 | 0.7111 |
| 3.0853        | 31.0  | 2666 | 2.4664          | 0.9575 | 0.7383 |
| 3.1276        | 32.0  | 2752 | 2.3562          | 0.9609 | 0.7277 |
| 3.0271        | 33.0  | 2838 | 2.3270          | 0.9633 | 0.7301 |
| 2.6923        | 34.0  | 2924 | 2.1691          | 0.9694 | 0.6807 |
| 2.219         | 35.0  | 3010 | 1.4645          | 0.9589 | 0.4523 |
| 2.219         | 36.0  | 3096 | 0.8696          | 0.7098 | 0.2029 |
| 1.5882        | 37.0  | 3182 | 0.5418          | 0.3871 | 0.1043 |
| 1.0408        | 38.0  | 3268 | 0.3795          | 0.2535 | 0.0727 |
| 0.7398        | 39.0  | 3354 | 0.3286          | 0.2129 | 0.0623 |
| 0.6218        | 40.0  | 3440 | 0.2955          | 0.1905 | 0.0563 |
| 0.5638        | 41.0  | 3526 | 0.2789          | 0.1830 | 0.0536 |
| 0.4704        | 42.0  | 3612 | 0.2561          | 0.1570 | 0.0480 |
| 0.4704        | 43.0  | 3698 | 0.2428          | 0.1519 | 0.0464 |
| 0.43          | 44.0  | 3784 | 0.2288          | 0.1400 | 0.0431 |
| 0.4286        | 45.0  | 3870 | 0.2181          | 0.1366 | 0.0412 |
| 0.3898        | 46.0  | 3956 | 0.2135          | 0.1290 | 0.0406 |
| 0.3693        | 47.0  | 4042 | 0.2044          | 0.1339 | 0.0399 |
| 0.3608        | 48.0  | 4128 | 0.1976          | 0.1286 | 0.0389 |
| 0.3557        | 49.0  | 4214 | 0.1996          | 0.1276 | 0.0385 |
| 0.3065        | 50.0  | 4300 | 0.1934          | 0.1278 | 0.0376 |
| 0.3065        | 51.0  | 4386 | 0.1894          | 0.1235 | 0.0373 |
| 0.3169        | 52.0  | 4472 | 0.1845          | 0.1220 | 0.0368 |
| 0.305         | 53.0  | 4558 | 0.1789          | 0.1191 | 0.0358 |
| 0.2883        | 54.0  | 4644 | 0.1837          | 0.1162 | 0.0352 |
| 0.2888        | 55.0  | 4730 | 0.1843          | 0.1152 | 0.0355 |
| 0.2871        | 56.0  | 4816 | 0.1782          | 0.1152 | 0.0349 |
| 0.2616        | 57.0  | 4902 | 0.1695          | 0.1120 | 0.0342 |
| 0.2616        | 58.0  | 4988 | 0.1737          | 0.1115 | 0.0336 |
| 0.2768        | 59.0  | 5074 | 0.1713          | 0.1130 | 0.0340 |
| 0.2649        | 60.0  | 5160 | 0.1605          | 0.1098 | 0.0332 |
| 0.2633        | 61.0  | 5246 | 0.1652          | 0.1079 | 0.0326 |
| 0.2471        | 62.0  | 5332 | 0.1635          | 0.1074 | 0.0324 |
| 0.2488        | 63.0  | 5418 | 0.1596          | 0.1096 | 0.0331 |
| 0.2445        | 64.0  | 5504 | 0.1609          | 0.1043 | 0.0313 |
| 0.2445        | 65.0  | 5590 | 0.1646          | 0.1074 | 0.0324 |
| 0.2443        | 66.0  | 5676 | 0.1557          | 0.1079 | 0.0323 |
| 0.2242        | 67.0  | 5762 | 0.1616          | 0.1055 | 0.0316 |
| 0.233         | 68.0  | 5848 | 0.1589          | 0.1057 | 0.0319 |
| 0.2342        | 69.0  | 5934 | 0.1617          | 0.1069 | 0.0321 |
| 0.2042        | 70.0  | 6020 | 0.1548          | 0.1067 | 0.0321 |
| 0.2193        | 71.0  | 6106 | 0.1559          | 0.1074 | 0.0319 |
| 0.2193        | 72.0  | 6192 | 0.1529          | 0.1094 | 0.0328 |
| 0.2155        | 73.0  | 6278 | 0.1526          | 0.1050 | 0.0313 |
| 0.2071        | 74.0  | 6364 | 0.1525          | 0.1062 | 0.0315 |
| 0.2211        | 75.0  | 6450 | 0.1517          | 0.1033 | 0.0310 |
| 0.2111        | 76.0  | 6536 | 0.1525          | 0.1040 | 0.0311 |
| 0.2222        | 77.0  | 6622 | 0.1538          | 0.1033 | 0.0307 |
| 0.2277        | 78.0  | 6708 | 0.1508          | 0.1043 | 0.0313 |
| 0.2277        | 79.0  | 6794 | 0.1514          | 0.1062 | 0.0314 |
| 0.2073        | 80.0  | 6880 | 0.1531          | 0.1050 | 0.0314 |
| 0.1858        | 81.0  | 6966 | 0.1516          | 0.1045 | 0.0314 |
| 0.2002        | 82.0  | 7052 | 0.1538          | 0.1030 | 0.0307 |
| 0.1882        | 83.0  | 7138 | 0.1519          | 0.1026 | 0.0309 |
| 0.2001        | 84.0  | 7224 | 0.1556          | 0.1023 | 0.0309 |
| 0.1855        | 85.0  | 7310 | 0.1525          | 0.1023 | 0.0307 |
| 0.1855        | 86.0  | 7396 | 0.1527          | 0.1023 | 0.0312 |
| 0.201         | 87.0  | 7482 | 0.1510          | 0.1050 | 0.0315 |
| 0.1997        | 88.0  | 7568 | 0.1524          | 0.1026 | 0.0314 |
| 0.1925        | 89.0  | 7654 | 0.1525          | 0.1040 | 0.0317 |
| 0.1969        | 90.0  | 7740 | 0.1554          | 0.1033 | 0.0316 |
| 0.1852        | 91.0  | 7826 | 0.1552          | 0.1038 | 0.0315 |
| 0.1922        | 92.0  | 7912 | 0.1540          | 0.1026 | 0.0310 |
| 0.1922        | 93.0  | 7998 | 0.1523          | 0.1030 | 0.0313 |
| 0.1842        | 94.0  | 8084 | 0.1527          | 0.1023 | 0.0310 |
| 0.1839        | 95.0  | 8170 | 0.1514          | 0.1013 | 0.0309 |
| 0.189         | 96.0  | 8256 | 0.1515          | 0.1018 | 0.0310 |
| 0.1945        | 97.0  | 8342 | 0.1528          | 0.1018 | 0.0310 |
| 0.1766        | 98.0  | 8428 | 0.1515          | 0.1026 | 0.0312 |


### 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-07", "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-07
==================================================


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: 0.1508
* Wer: 0.1043
* Cer: 0.0313


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