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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-02

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: 0.1200
- Wer: 0.0899
- Cer: 0.0254

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 26.4293       | 1.0   | 67   | 3.4414          | 1.0    | 1.0    |
| 7.9769        | 2.0   | 134  | 2.9984          | 1.0    | 1.0    |
| 3.0417        | 3.0   | 201  | 2.9436          | 1.0    | 1.0    |
| 3.0417        | 4.0   | 268  | 2.9027          | 1.0    | 1.0    |
| 2.9268        | 5.0   | 335  | 2.8924          | 1.0    | 1.0    |
| 2.8996        | 6.0   | 402  | 2.8828          | 1.0    | 1.0    |
| 2.8996        | 7.0   | 469  | 2.7512          | 1.0    | 1.0    |
| 2.8007        | 8.0   | 536  | 1.4882          | 0.9308 | 0.3579 |
| 1.7472        | 9.0   | 603  | 0.5752          | 0.3096 | 0.0792 |
| 1.7472        | 10.0  | 670  | 0.3713          | 0.2030 | 0.0519 |
| 0.7469        | 11.0  | 737  | 0.3007          | 0.1633 | 0.0438 |
| 0.5658        | 12.0  | 804  | 0.2614          | 0.1563 | 0.0411 |
| 0.5658        | 13.0  | 871  | 0.2246          | 0.1359 | 0.0362 |
| 0.4483        | 14.0  | 938  | 0.2101          | 0.1235 | 0.0337 |
| 0.3807        | 15.0  | 1005 | 0.1966          | 0.1228 | 0.0339 |
| 0.3807        | 16.0  | 1072 | 0.1845          | 0.1114 | 0.0312 |
| 0.352         | 17.0  | 1139 | 0.1803          | 0.1072 | 0.0319 |
| 0.3203        | 18.0  | 1206 | 0.1737          | 0.1045 | 0.0301 |
| 0.3203        | 19.0  | 1273 | 0.1614          | 0.1017 | 0.0296 |
| 0.2915        | 20.0  | 1340 | 0.1501          | 0.1013 | 0.0288 |
| 0.2897        | 21.0  | 1407 | 0.1532          | 0.0979 | 0.0287 |
| 0.2897        | 22.0  | 1474 | 0.1478          | 0.0993 | 0.0281 |
| 0.2601        | 23.0  | 1541 | 0.1445          | 0.0979 | 0.0283 |
| 0.2427        | 24.0  | 1608 | 0.1434          | 0.1017 | 0.0285 |
| 0.2427        | 25.0  | 1675 | 0.1425          | 0.0965 | 0.0277 |
| 0.2385        | 26.0  | 1742 | 0.1423          | 0.0986 | 0.0282 |
| 0.229         | 27.0  | 1809 | 0.1427          | 0.0969 | 0.0275 |
| 0.229         | 28.0  | 1876 | 0.1368          | 0.0948 | 0.0266 |
| 0.2084        | 29.0  | 1943 | 0.1383          | 0.0975 | 0.0274 |
| 0.2027        | 30.0  | 2010 | 0.1370          | 0.0948 | 0.0274 |
| 0.2027        | 31.0  | 2077 | 0.1386          | 0.0969 | 0.0275 |
| 0.1956        | 32.0  | 2144 | 0.1337          | 0.0979 | 0.0277 |
| 0.2027        | 33.0  | 2211 | 0.1332          | 0.0955 | 0.0273 |
| 0.2027        | 34.0  | 2278 | 0.1361          | 0.0930 | 0.0274 |
| 0.1834        | 35.0  | 2345 | 0.1345          | 0.0910 | 0.0268 |
| 0.1874        | 36.0  | 2412 | 0.1311          | 0.0969 | 0.0275 |
| 0.1874        | 37.0  | 2479 | 0.1331          | 0.0913 | 0.0263 |
| 0.1739        | 38.0  | 2546 | 0.1296          | 0.0886 | 0.0257 |
| 0.1671        | 39.0  | 2613 | 0.1321          | 0.0906 | 0.0255 |
| 0.1671        | 40.0  | 2680 | 0.1306          | 0.0927 | 0.0260 |
| 0.1695        | 41.0  | 2747 | 0.1336          | 0.0937 | 0.0270 |
| 0.1608        | 42.0  | 2814 | 0.1291          | 0.0861 | 0.0254 |
| 0.1608        | 43.0  | 2881 | 0.1328          | 0.0910 | 0.0265 |
| 0.1577        | 44.0  | 2948 | 0.1300          | 0.0913 | 0.0259 |
| 0.1674        | 45.0  | 3015 | 0.1297          | 0.0906 | 0.0263 |
| 0.1674        | 46.0  | 3082 | 0.1279          | 0.0882 | 0.0261 |
| 0.1658        | 47.0  | 3149 | 0.1287          | 0.0924 | 0.0258 |
| 0.1588        | 48.0  | 3216 | 0.1275          | 0.0906 | 0.0266 |
| 0.1588        | 49.0  | 3283 | 0.1303          | 0.0917 | 0.0264 |
| 0.1403        | 50.0  | 3350 | 0.1267          | 0.0913 | 0.0264 |
| 0.1686        | 51.0  | 3417 | 0.1265          | 0.0896 | 0.0259 |
| 0.1686        | 52.0  | 3484 | 0.1286          | 0.0930 | 0.0265 |
| 0.1427        | 53.0  | 3551 | 0.1261          | 0.0899 | 0.0264 |
| 0.152         | 54.0  | 3618 | 0.1288          | 0.0889 | 0.0259 |
| 0.152         | 55.0  | 3685 | 0.1259          | 0.0882 | 0.0257 |
| 0.1516        | 56.0  | 3752 | 0.1263          | 0.0913 | 0.0262 |
| 0.1394        | 57.0  | 3819 | 0.1239          | 0.0910 | 0.0257 |
| 0.1394        | 58.0  | 3886 | 0.1236          | 0.0872 | 0.0254 |
| 0.1514        | 59.0  | 3953 | 0.1253          | 0.0903 | 0.0259 |
| 0.1252        | 60.0  | 4020 | 0.1217          | 0.0889 | 0.0257 |
| 0.1252        | 61.0  | 4087 | 0.1212          | 0.0899 | 0.0256 |
| 0.143         | 62.0  | 4154 | 0.1228          | 0.0896 | 0.0252 |
| 0.139         | 63.0  | 4221 | 0.1210          | 0.0886 | 0.0251 |
| 0.139         | 64.0  | 4288 | 0.1217          | 0.0896 | 0.0256 |
| 0.1398        | 65.0  | 4355 | 0.1225          | 0.0899 | 0.0256 |
| 0.1348        | 66.0  | 4422 | 0.1222          | 0.0875 | 0.0252 |
| 0.1348        | 67.0  | 4489 | 0.1231          | 0.0875 | 0.0254 |
| 0.1284        | 68.0  | 4556 | 0.1200          | 0.0899 | 0.0254 |
| 0.1307        | 69.0  | 4623 | 0.1231          | 0.0879 | 0.0254 |
| 0.1307        | 70.0  | 4690 | 0.1231          | 0.0879 | 0.0252 |
| 0.1251        | 71.0  | 4757 | 0.1225          | 0.0872 | 0.0256 |
| 0.136         | 72.0  | 4824 | 0.1218          | 0.0889 | 0.0254 |
| 0.136         | 73.0  | 4891 | 0.1222          | 0.0868 | 0.0246 |
| 0.1394        | 74.0  | 4958 | 0.1210          | 0.0920 | 0.0264 |
| 0.127         | 75.0  | 5025 | 0.1218          | 0.0913 | 0.0257 |
| 0.127         | 76.0  | 5092 | 0.1221          | 0.0892 | 0.0252 |
| 0.1223        | 77.0  | 5159 | 0.1229          | 0.0882 | 0.0256 |
| 0.1247        | 78.0  | 5226 | 0.1216          | 0.0882 | 0.0257 |
| 0.1247        | 79.0  | 5293 | 0.1225          | 0.0899 | 0.0259 |
| 0.131         | 80.0  | 5360 | 0.1224          | 0.0889 | 0.0257 |
| 0.1127        | 81.0  | 5427 | 0.1244          | 0.0906 | 0.0258 |
| 0.1127        | 82.0  | 5494 | 0.1226          | 0.0886 | 0.0256 |
| 0.1154        | 83.0  | 5561 | 0.1222          | 0.0899 | 0.0258 |
| 0.1233        | 84.0  | 5628 | 0.1236          | 0.0889 | 0.0257 |
| 0.1233        | 85.0  | 5695 | 0.1219          | 0.0903 | 0.0261 |
| 0.1299        | 86.0  | 5762 | 0.1222          | 0.0875 | 0.0257 |
| 0.112         | 87.0  | 5829 | 0.1215          | 0.0903 | 0.0261 |
| 0.112         | 88.0  | 5896 | 0.1229          | 0.0913 | 0.0259 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-02", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us