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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-03

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: 0.1342
- Wer: 0.0814
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.7197       | 1.0   | 86   | 7.8136          | 1.0    | 0.9778 |
| 12.9844       | 2.0   | 172  | 3.2566          | 1.0    | 1.0    |
| 5.5212        | 3.0   | 258  | 2.9239          | 1.0    | 1.0    |
| 3.0047        | 4.0   | 344  | 2.9117          | 1.0    | 1.0    |
| 2.92          | 5.0   | 430  | 2.8873          | 1.0    | 1.0    |
| 2.8994        | 6.0   | 516  | 2.8767          | 1.0    | 1.0    |
| 2.8914        | 7.0   | 602  | 2.8744          | 1.0    | 1.0    |
| 2.8914        | 8.0   | 688  | 2.7465          | 1.0    | 1.0    |
| 2.8674        | 9.0   | 774  | 1.6305          | 1.0    | 0.5600 |
| 2.278         | 10.0  | 860  | 0.5303          | 0.3196 | 0.0788 |
| 1.0525        | 11.0  | 946  | 0.3310          | 0.1926 | 0.0524 |
| 0.6335        | 12.0  | 1032 | 0.2698          | 0.1597 | 0.0454 |
| 0.5092        | 13.0  | 1118 | 0.2393          | 0.1413 | 0.0410 |
| 0.4302        | 14.0  | 1204 | 0.2231          | 0.1275 | 0.0393 |
| 0.4302        | 15.0  | 1290 | 0.2089          | 0.1227 | 0.0376 |
| 0.3908        | 16.0  | 1376 | 0.1960          | 0.1146 | 0.0355 |
| 0.3692        | 17.0  | 1462 | 0.1816          | 0.1038 | 0.0325 |
| 0.3152        | 18.0  | 1548 | 0.1774          | 0.1067 | 0.0334 |
| 0.2978        | 19.0  | 1634 | 0.1765          | 0.1007 | 0.0320 |
| 0.2845        | 20.0  | 1720 | 0.1700          | 0.0981 | 0.0308 |
| 0.2807        | 21.0  | 1806 | 0.1688          | 0.0998 | 0.0313 |
| 0.2807        | 22.0  | 1892 | 0.1620          | 0.0984 | 0.0308 |
| 0.2485        | 23.0  | 1978 | 0.1561          | 0.0962 | 0.0304 |
| 0.2459        | 24.0  | 2064 | 0.1558          | 0.0950 | 0.0303 |
| 0.2515        | 25.0  | 2150 | 0.1543          | 0.0948 | 0.0297 |
| 0.2161        | 26.0  | 2236 | 0.1518          | 0.0948 | 0.0302 |
| 0.2185        | 27.0  | 2322 | 0.1452          | 0.0921 | 0.0284 |
| 0.2224        | 28.0  | 2408 | 0.1468          | 0.0912 | 0.0284 |
| 0.2224        | 29.0  | 2494 | 0.1455          | 0.0926 | 0.0283 |
| 0.225         | 30.0  | 2580 | 0.1455          | 0.0931 | 0.0285 |
| 0.2025        | 31.0  | 2666 | 0.1472          | 0.0914 | 0.0282 |
| 0.2011        | 32.0  | 2752 | 0.1423          | 0.0912 | 0.0278 |
| 0.1886        | 33.0  | 2838 | 0.1433          | 0.0914 | 0.0282 |
| 0.1912        | 34.0  | 2924 | 0.1446          | 0.0867 | 0.0281 |
| 0.1878        | 35.0  | 3010 | 0.1403          | 0.0890 | 0.0276 |
| 0.1878        | 36.0  | 3096 | 0.1412          | 0.0888 | 0.0275 |
| 0.1875        | 37.0  | 3182 | 0.1420          | 0.0862 | 0.0274 |
| 0.1757        | 38.0  | 3268 | 0.1447          | 0.0898 | 0.0283 |
| 0.1809        | 39.0  | 3354 | 0.1403          | 0.0883 | 0.0274 |
| 0.185         | 40.0  | 3440 | 0.1406          | 0.0878 | 0.0277 |
| 0.1773        | 41.0  | 3526 | 0.1397          | 0.0840 | 0.0271 |
| 0.1607        | 42.0  | 3612 | 0.1403          | 0.0910 | 0.0280 |
| 0.1607        | 43.0  | 3698 | 0.1424          | 0.0910 | 0.0280 |
| 0.1686        | 44.0  | 3784 | 0.1401          | 0.0886 | 0.0276 |
| 0.1651        | 45.0  | 3870 | 0.1403          | 0.0869 | 0.0270 |
| 0.1494        | 46.0  | 3956 | 0.1419          | 0.0886 | 0.0273 |
| 0.1665        | 47.0  | 4042 | 0.1429          | 0.0869 | 0.0270 |
| 0.1591        | 48.0  | 4128 | 0.1397          | 0.0878 | 0.0274 |
| 0.1426        | 49.0  | 4214 | 0.1416          | 0.0862 | 0.0272 |
| 0.1496        | 50.0  | 4300 | 0.1406          | 0.0847 | 0.0267 |
| 0.1496        | 51.0  | 4386 | 0.1414          | 0.0845 | 0.0270 |
| 0.172         | 52.0  | 4472 | 0.1382          | 0.0855 | 0.0272 |
| 0.152         | 53.0  | 4558 | 0.1395          | 0.0869 | 0.0271 |
| 0.1548        | 54.0  | 4644 | 0.1394          | 0.0871 | 0.0272 |
| 0.1453        | 55.0  | 4730 | 0.1373          | 0.0816 | 0.0255 |
| 0.1445        | 56.0  | 4816 | 0.1395          | 0.0838 | 0.0264 |
| 0.1334        | 57.0  | 4902 | 0.1373          | 0.0864 | 0.0267 |
| 0.1334        | 58.0  | 4988 | 0.1360          | 0.0850 | 0.0265 |
| 0.1381        | 59.0  | 5074 | 0.1404          | 0.0847 | 0.0265 |
| 0.1326        | 60.0  | 5160 | 0.1386          | 0.0857 | 0.0266 |
| 0.1355        | 61.0  | 5246 | 0.1364          | 0.0821 | 0.0263 |
| 0.1356        | 62.0  | 5332 | 0.1394          | 0.0838 | 0.0263 |
| 0.1264        | 63.0  | 5418 | 0.1413          | 0.0831 | 0.0260 |
| 0.1268        | 64.0  | 5504 | 0.1369          | 0.0795 | 0.0254 |
| 0.1268        | 65.0  | 5590 | 0.1377          | 0.0819 | 0.0259 |
| 0.1295        | 66.0  | 5676 | 0.1368          | 0.0819 | 0.0259 |
| 0.1272        | 67.0  | 5762 | 0.1390          | 0.0828 | 0.0259 |
| 0.1578        | 68.0  | 5848 | 0.1377          | 0.0836 | 0.0260 |
| 0.1286        | 69.0  | 5934 | 0.1356          | 0.0800 | 0.0252 |
| 0.1248        | 70.0  | 6020 | 0.1357          | 0.0840 | 0.0262 |
| 0.12          | 71.0  | 6106 | 0.1367          | 0.0819 | 0.0259 |
| 0.12          | 72.0  | 6192 | 0.1386          | 0.0824 | 0.0256 |
| 0.1268        | 73.0  | 6278 | 0.1358          | 0.0838 | 0.0261 |
| 0.1246        | 74.0  | 6364 | 0.1368          | 0.0831 | 0.0260 |
| 0.117         | 75.0  | 6450 | 0.1356          | 0.0824 | 0.0255 |
| 0.1256        | 76.0  | 6536 | 0.1355          | 0.0816 | 0.0253 |
| 0.1361        | 77.0  | 6622 | 0.1358          | 0.0836 | 0.0259 |
| 0.1158        | 78.0  | 6708 | 0.1356          | 0.0807 | 0.0255 |
| 0.1158        | 79.0  | 6794 | 0.1360          | 0.0788 | 0.0248 |
| 0.1338        | 80.0  | 6880 | 0.1360          | 0.0793 | 0.0253 |
| 0.117         | 81.0  | 6966 | 0.1352          | 0.0785 | 0.0248 |
| 0.1123        | 82.0  | 7052 | 0.1342          | 0.0814 | 0.0252 |
| 0.1232        | 83.0  | 7138 | 0.1357          | 0.0831 | 0.0256 |
| 0.1178        | 84.0  | 7224 | 0.1348          | 0.0800 | 0.0252 |
| 0.1151        | 85.0  | 7310 | 0.1354          | 0.0819 | 0.0253 |
| 0.1151        | 86.0  | 7396 | 0.1350          | 0.0804 | 0.0251 |
| 0.1211        | 87.0  | 7482 | 0.1365          | 0.0816 | 0.0253 |
| 0.1079        | 88.0  | 7568 | 0.1359          | 0.0802 | 0.0252 |
| 0.1201        | 89.0  | 7654 | 0.1368          | 0.0833 | 0.0254 |
| 0.1073        | 90.0  | 7740 | 0.1361          | 0.0819 | 0.0252 |
| 0.1088        | 91.0  | 7826 | 0.1358          | 0.0819 | 0.0252 |
| 0.1156        | 92.0  | 7912 | 0.1354          | 0.0804 | 0.0251 |
| 0.1156        | 93.0  | 7998 | 0.1358          | 0.0802 | 0.0249 |
| 0.113         | 94.0  | 8084 | 0.1357          | 0.0795 | 0.0249 |
| 0.1138        | 95.0  | 8170 | 0.1357          | 0.0812 | 0.0251 |
| 0.1144        | 96.0  | 8256 | 0.1352          | 0.0812 | 0.0251 |
| 0.1041        | 97.0  | 8342 | 0.1350          | 0.0802 | 0.0249 |
| 0.1103        | 98.0  | 8428 | 0.1353          | 0.0809 | 0.0250 |
| 0.1056        | 99.0  | 8514 | 0.1349          | 0.0812 | 0.0251 |
| 0.1019        | 100.0 | 8600 | 0.1349          | 0.0804 | 0.0250 |


### 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-03", "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-03
==================================================


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: 0.1342
* Wer: 0.0814
* 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