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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-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: 0.1531
- Wer: 0.0951
- Cer: 0.0280

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.9637       | 1.0   | 67   | 7.7844          | 0.9680 | 0.9846 |
| 10.0192       | 2.0   | 134  | 6.8622          | 0.9613 | 0.9448 |
| 4.9566        | 3.0   | 201  | 6.6997          | 0.9617 | 0.9567 |
| 4.9566        | 4.0   | 268  | 6.8259          | 0.9662 | 0.9720 |
| 4.4483        | 5.0   | 335  | 6.8626          | 0.9680 | 0.9780 |
| 4.2073        | 6.0   | 402  | 5.6960          | 0.9732 | 0.9821 |
| 4.2073        | 7.0   | 469  | 6.6086          | 0.9728 | 0.9818 |
| 4.077         | 8.0   | 536  | 6.2581          | 0.9714 | 0.9821 |
| 3.7594        | 9.0   | 603  | 6.0266          | 0.9718 | 0.9827 |
| 3.7594        | 10.0  | 670  | 5.7485          | 0.9756 | 0.9795 |
| 3.7788        | 11.0  | 737  | 5.0587          | 0.9714 | 0.9816 |
| 3.6071        | 12.0  | 804  | 4.7627          | 0.9714 | 0.9827 |
| 3.6071        | 13.0  | 871  | 3.5214          | 0.9725 | 0.9820 |
| 3.3363        | 14.0  | 938  | 2.9877          | 0.9753 | 0.9798 |
| 3.1039        | 15.0  | 1005 | 2.9151          | 0.9805 | 0.9840 |
| 3.1039        | 16.0  | 1072 | 2.8843          | 0.9847 | 0.9909 |
| 2.9064        | 17.0  | 1139 | 2.8720          | 0.9857 | 0.9846 |
| 2.8703        | 18.0  | 1206 | 2.7859          | 0.9972 | 0.9364 |
| 2.8703        | 19.0  | 1273 | 2.5571          | 1.0    | 0.8941 |
| 2.6946        | 20.0  | 1340 | 1.6485          | 0.9944 | 0.4890 |
| 1.8247        | 21.0  | 1407 | 0.7422          | 0.7133 | 0.1540 |
| 1.8247        | 22.0  | 1474 | 0.4440          | 0.3640 | 0.0807 |
| 0.8703        | 23.0  | 1541 | 0.3507          | 0.2090 | 0.0564 |
| 0.5944        | 24.0  | 1608 | 0.3083          | 0.1881 | 0.0500 |
| 0.5944        | 25.0  | 1675 | 0.2676          | 0.1721 | 0.0456 |
| 0.4905        | 26.0  | 1742 | 0.2580          | 0.1536 | 0.0428 |
| 0.4306        | 27.0  | 1809 | 0.2281          | 0.1428 | 0.0391 |
| 0.4306        | 28.0  | 1876 | 0.2203          | 0.1299 | 0.0364 |
| 0.356         | 29.0  | 1943 | 0.2066          | 0.1250 | 0.0352 |
| 0.3299        | 30.0  | 2010 | 0.2104          | 0.1177 | 0.0335 |
| 0.3299        | 31.0  | 2077 | 0.2006          | 0.1181 | 0.0330 |
| 0.3279        | 32.0  | 2144 | 0.1907          | 0.1181 | 0.0335 |
| 0.293         | 33.0  | 2211 | 0.1819          | 0.1135 | 0.0322 |
| 0.293         | 34.0  | 2278 | 0.1876          | 0.1097 | 0.0320 |
| 0.2869        | 35.0  | 2345 | 0.1862          | 0.1083 | 0.0311 |
| 0.2771        | 36.0  | 2412 | 0.1806          | 0.1160 | 0.0323 |
| 0.2771        | 37.0  | 2479 | 0.1757          | 0.1087 | 0.0311 |
| 0.2668        | 38.0  | 2546 | 0.1799          | 0.1052 | 0.0308 |
| 0.2394        | 39.0  | 2613 | 0.1840          | 0.1059 | 0.0313 |
| 0.2394        | 40.0  | 2680 | 0.1826          | 0.1031 | 0.0303 |
| 0.2269        | 41.0  | 2747 | 0.1759          | 0.1059 | 0.0312 |
| 0.2153        | 42.0  | 2814 | 0.1822          | 0.1024 | 0.0308 |
| 0.2153        | 43.0  | 2881 | 0.1667          | 0.1021 | 0.0305 |
| 0.238         | 44.0  | 2948 | 0.1757          | 0.1021 | 0.0308 |
| 0.2251        | 45.0  | 3015 | 0.1704          | 0.1031 | 0.0306 |
| 0.2251        | 46.0  | 3082 | 0.1809          | 0.1000 | 0.0299 |
| 0.2196        | 47.0  | 3149 | 0.1676          | 0.1000 | 0.0307 |
| 0.1932        | 48.0  | 3216 | 0.1658          | 0.1007 | 0.0300 |
| 0.1932        | 49.0  | 3283 | 0.1652          | 0.1000 | 0.0299 |
| 0.199         | 50.0  | 3350 | 0.1720          | 0.0993 | 0.0303 |
| 0.199         | 51.0  | 3417 | 0.1619          | 0.1021 | 0.0305 |
| 0.199         | 52.0  | 3484 | 0.1642          | 0.0986 | 0.0295 |
| 0.1747        | 53.0  | 3551 | 0.1655          | 0.1000 | 0.0299 |
| 0.1785        | 54.0  | 3618 | 0.1697          | 0.0965 | 0.0292 |
| 0.1785        | 55.0  | 3685 | 0.1605          | 0.0993 | 0.0294 |
| 0.1734        | 56.0  | 3752 | 0.1693          | 0.0979 | 0.0293 |
| 0.1813        | 57.0  | 3819 | 0.1658          | 0.0968 | 0.0292 |
| 0.1813        | 58.0  | 3886 | 0.1638          | 0.0996 | 0.0298 |
| 0.1718        | 59.0  | 3953 | 0.1705          | 0.0961 | 0.0290 |
| 0.1646        | 60.0  | 4020 | 0.1678          | 0.0965 | 0.0286 |
| 0.1646        | 61.0  | 4087 | 0.1647          | 0.0989 | 0.0288 |
| 0.1706        | 62.0  | 4154 | 0.1598          | 0.1010 | 0.0291 |
| 0.1559        | 63.0  | 4221 | 0.1555          | 0.0982 | 0.0288 |
| 0.1559        | 64.0  | 4288 | 0.1622          | 0.0965 | 0.0285 |
| 0.171         | 65.0  | 4355 | 0.1678          | 0.0940 | 0.0288 |
| 0.1655        | 66.0  | 4422 | 0.1643          | 0.0913 | 0.0281 |
| 0.1655        | 67.0  | 4489 | 0.1618          | 0.0947 | 0.0281 |
| 0.1628        | 68.0  | 4556 | 0.1587          | 0.0947 | 0.0283 |
| 0.149         | 69.0  | 4623 | 0.1614          | 0.0954 | 0.0281 |
| 0.149         | 70.0  | 4690 | 0.1636          | 0.0951 | 0.0280 |
| 0.1531        | 71.0  | 4757 | 0.1584          | 0.0989 | 0.0284 |
| 0.1677        | 72.0  | 4824 | 0.1638          | 0.0958 | 0.0284 |
| 0.1677        | 73.0  | 4891 | 0.1608          | 0.0947 | 0.0277 |
| 0.153         | 74.0  | 4958 | 0.1579          | 0.0951 | 0.0276 |
| 0.1464        | 75.0  | 5025 | 0.1633          | 0.0961 | 0.0280 |
| 0.1464        | 76.0  | 5092 | 0.1561          | 0.0958 | 0.0277 |
| 0.1533        | 77.0  | 5159 | 0.1554          | 0.0944 | 0.0279 |
| 0.1487        | 78.0  | 5226 | 0.1617          | 0.0930 | 0.0279 |
| 0.1487        | 79.0  | 5293 | 0.1574          | 0.0927 | 0.0274 |
| 0.1492        | 80.0  | 5360 | 0.1531          | 0.0951 | 0.0280 |
| 0.151         | 81.0  | 5427 | 0.1632          | 0.0954 | 0.0279 |
| 0.151         | 82.0  | 5494 | 0.1613          | 0.0972 | 0.0283 |
| 0.151         | 83.0  | 5561 | 0.1581          | 0.0968 | 0.0281 |
| 0.1398        | 84.0  | 5628 | 0.1569          | 0.0965 | 0.0278 |
| 0.1398        | 85.0  | 5695 | 0.1586          | 0.0968 | 0.0283 |
| 0.1344        | 86.0  | 5762 | 0.1595          | 0.0951 | 0.0280 |
| 0.1367        | 87.0  | 5829 | 0.1594          | 0.0937 | 0.0277 |
| 0.1367        | 88.0  | 5896 | 0.1583          | 0.0954 | 0.0282 |
| 0.1543        | 89.0  | 5963 | 0.1604          | 0.0968 | 0.0281 |
| 0.134         | 90.0  | 6030 | 0.1607          | 0.0923 | 0.0274 |
| 0.134         | 91.0  | 6097 | 0.1578          | 0.0944 | 0.0278 |
| 0.1498        | 92.0  | 6164 | 0.1595          | 0.0951 | 0.0280 |
| 0.133         | 93.0  | 6231 | 0.1557          | 0.0968 | 0.0282 |
| 0.133         | 94.0  | 6298 | 0.1598          | 0.0951 | 0.0277 |
| 0.1487        | 95.0  | 6365 | 0.1576          | 0.0940 | 0.0278 |
| 0.1343        | 96.0  | 6432 | 0.1558          | 0.0944 | 0.0280 |
| 0.1343        | 97.0  | 6499 | 0.1561          | 0.0951 | 0.0280 |
| 0.132         | 98.0  | 6566 | 0.1570          | 0.0933 | 0.0276 |
| 0.1416        | 99.0  | 6633 | 0.1574          | 0.0930 | 0.0274 |
| 0.13          | 100.0 | 6700 | 0.1574          | 0.0930 | 0.0275 |


### 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-01", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us