transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-08
  results: []
---

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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-08

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: 0.1396
- Wer: 0.0828
- Cer: 0.0228

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 24.4898       | 1.0   | 67   | 6.6473          | 0.9805 | 0.9854 |
| 9.6476        | 2.0   | 134  | 5.1478          | 0.9775 | 0.9099 |
| 4.5647        | 3.0   | 201  | 4.9501          | 0.9510 | 0.9337 |
| 4.5647        | 4.0   | 268  | 4.7350          | 0.9821 | 0.9839 |
| 4.3107        | 5.0   | 335  | 4.7791          | 0.9818 | 0.9844 |
| 3.7636        | 6.0   | 402  | 4.6615          | 0.9834 | 0.9822 |
| 3.7636        | 7.0   | 469  | 4.4064          | 0.9854 | 0.9812 |
| 3.7891        | 8.0   | 536  | 4.1056          | 0.9868 | 0.9802 |
| 3.6656        | 9.0   | 603  | 3.1128          | 0.9983 | 0.9985 |
| 3.6656        | 10.0  | 670  | 2.9065          | 1.0    | 1.0    |
| 2.993         | 11.0  | 737  | 2.9184          | 1.0    | 1.0    |
| 2.8999        | 12.0  | 804  | 2.8963          | 1.0    | 1.0    |
| 2.8999        | 13.0  | 871  | 2.8663          | 1.0    | 1.0    |
| 2.879         | 14.0  | 938  | 2.7503          | 0.9977 | 0.9611 |
| 2.7677        | 15.0  | 1005 | 2.4108          | 1.0    | 0.9086 |
| 2.7677        | 16.0  | 1072 | 1.4958          | 1.0    | 0.5039 |
| 2.0951        | 17.0  | 1139 | 0.6763          | 0.6216 | 0.1321 |
| 1.0513        | 18.0  | 1206 | 0.4002          | 0.2890 | 0.0650 |
| 1.0513        | 19.0  | 1273 | 0.3120          | 0.1867 | 0.0468 |
| 0.6513        | 20.0  | 1340 | 0.2679          | 0.1718 | 0.0431 |
| 0.5148        | 21.0  | 1407 | 0.2419          | 0.1470 | 0.0391 |
| 0.5148        | 22.0  | 1474 | 0.2191          | 0.1261 | 0.0349 |
| 0.399         | 23.0  | 1541 | 0.1997          | 0.1225 | 0.0322 |
| 0.3708        | 24.0  | 1608 | 0.1961          | 0.1125 | 0.0313 |
| 0.3708        | 25.0  | 1675 | 0.1906          | 0.1102 | 0.0305 |
| 0.3342        | 26.0  | 1742 | 0.1841          | 0.1066 | 0.0303 |
| 0.3053        | 27.0  | 1809 | 0.1758          | 0.1039 | 0.0289 |
| 0.3053        | 28.0  | 1876 | 0.1696          | 0.0983 | 0.0270 |
| 0.2732        | 29.0  | 1943 | 0.1645          | 0.1033 | 0.0277 |
| 0.258         | 30.0  | 2010 | 0.1623          | 0.0953 | 0.0272 |
| 0.258         | 31.0  | 2077 | 0.1615          | 0.0943 | 0.0269 |
| 0.2489        | 32.0  | 2144 | 0.1591          | 0.0920 | 0.0262 |
| 0.2533        | 33.0  | 2211 | 0.1553          | 0.0920 | 0.0259 |
| 0.2533        | 34.0  | 2278 | 0.1603          | 0.0897 | 0.0255 |
| 0.2413        | 35.0  | 2345 | 0.1562          | 0.0910 | 0.0257 |
| 0.2377        | 36.0  | 2412 | 0.1544          | 0.0874 | 0.0252 |
| 0.2377        | 37.0  | 2479 | 0.1558          | 0.0884 | 0.0248 |
| 0.2189        | 38.0  | 2546 | 0.1520          | 0.0857 | 0.0243 |
| 0.2073        | 39.0  | 2613 | 0.1541          | 0.0857 | 0.0242 |
| 0.2073        | 40.0  | 2680 | 0.1495          | 0.0864 | 0.0244 |
| 0.204         | 41.0  | 2747 | 0.1497          | 0.0851 | 0.0243 |
| 0.198         | 42.0  | 2814 | 0.1516          | 0.0851 | 0.0247 |
| 0.198         | 43.0  | 2881 | 0.1498          | 0.0837 | 0.0238 |
| 0.1727        | 44.0  | 2948 | 0.1505          | 0.0894 | 0.0245 |
| 0.191         | 45.0  | 3015 | 0.1484          | 0.0844 | 0.0238 |
| 0.191         | 46.0  | 3082 | 0.1508          | 0.0847 | 0.0243 |
| 0.1922        | 47.0  | 3149 | 0.1494          | 0.0871 | 0.0243 |
| 0.1772        | 48.0  | 3216 | 0.1471          | 0.0904 | 0.0252 |
| 0.1772        | 49.0  | 3283 | 0.1477          | 0.0854 | 0.0242 |
| 0.17          | 50.0  | 3350 | 0.1463          | 0.0841 | 0.0239 |
| 0.1748        | 51.0  | 3417 | 0.1431          | 0.0841 | 0.0238 |
| 0.1748        | 52.0  | 3484 | 0.1454          | 0.0851 | 0.0232 |
| 0.1645        | 53.0  | 3551 | 0.1450          | 0.0884 | 0.0245 |
| 0.1808        | 54.0  | 3618 | 0.1425          | 0.0857 | 0.0233 |
| 0.1808        | 55.0  | 3685 | 0.1466          | 0.0828 | 0.0233 |
| 0.1712        | 56.0  | 3752 | 0.1442          | 0.0854 | 0.0235 |
| 0.1553        | 57.0  | 3819 | 0.1397          | 0.0841 | 0.0233 |
| 0.1553        | 58.0  | 3886 | 0.1418          | 0.0861 | 0.0241 |
| 0.1505        | 59.0  | 3953 | 0.1433          | 0.0831 | 0.0233 |
| 0.1609        | 60.0  | 4020 | 0.1439          | 0.0844 | 0.0234 |
| 0.1609        | 61.0  | 4087 | 0.1438          | 0.0837 | 0.0233 |
| 0.1521        | 62.0  | 4154 | 0.1433          | 0.0857 | 0.0237 |
| 0.1541        | 63.0  | 4221 | 0.1410          | 0.0861 | 0.0236 |
| 0.1541        | 64.0  | 4288 | 0.1396          | 0.0828 | 0.0228 |
| 0.1464        | 65.0  | 4355 | 0.1404          | 0.0824 | 0.0226 |
| 0.1489        | 66.0  | 4422 | 0.1423          | 0.0837 | 0.0232 |
| 0.1489        | 67.0  | 4489 | 0.1426          | 0.0847 | 0.0230 |
| 0.1513        | 68.0  | 4556 | 0.1407          | 0.0828 | 0.0228 |
| 0.1655        | 69.0  | 4623 | 0.1441          | 0.0877 | 0.0234 |
| 0.1655        | 70.0  | 4690 | 0.1446          | 0.0900 | 0.0241 |
| 0.1337        | 71.0  | 4757 | 0.1432          | 0.0844 | 0.0228 |
| 0.1471        | 72.0  | 4824 | 0.1456          | 0.0811 | 0.0225 |
| 0.1471        | 73.0  | 4891 | 0.1426          | 0.0781 | 0.0225 |
| 0.1527        | 74.0  | 4958 | 0.1438          | 0.0824 | 0.0227 |
| 0.1276        | 75.0  | 5025 | 0.1440          | 0.0811 | 0.0223 |
| 0.1276        | 76.0  | 5092 | 0.1431          | 0.0804 | 0.0225 |
| 0.1393        | 77.0  | 5159 | 0.1460          | 0.0834 | 0.0232 |
| 0.132         | 78.0  | 5226 | 0.1434          | 0.0811 | 0.0226 |
| 0.132         | 79.0  | 5293 | 0.1464          | 0.0808 | 0.0227 |
| 0.1326        | 80.0  | 5360 | 0.1444          | 0.0791 | 0.0222 |
| 0.1318        | 81.0  | 5427 | 0.1463          | 0.0788 | 0.0223 |
| 0.1318        | 82.0  | 5494 | 0.1448          | 0.0811 | 0.0227 |
| 0.1281        | 83.0  | 5561 | 0.1452          | 0.0811 | 0.0224 |
| 0.1294        | 84.0  | 5628 | 0.1420          | 0.0811 | 0.0225 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.13.3
