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-10
  results: []
---

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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-10

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: 0.1766
- Wer: 0.0913
- Cer: 0.0291

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 21.8058       | 1.0   | 67   | 8.5869          | 0.9997 | 0.9859 |
| 12.0549       | 2.0   | 134  | 5.9897          | 1.0    | 0.9719 |
| 5.5651        | 3.0   | 201  | 3.0869          | 1.0    | 1.0    |
| 5.5651        | 4.0   | 268  | 2.9406          | 1.0    | 1.0    |
| 2.9913        | 5.0   | 335  | 2.9153          | 1.0    | 1.0    |
| 2.9244        | 6.0   | 402  | 2.8824          | 1.0    | 1.0    |
| 2.9244        | 7.0   | 469  | 2.8784          | 1.0    | 1.0    |
| 2.8927        | 8.0   | 536  | 2.8759          | 1.0    | 1.0    |
| 2.8858        | 9.0   | 603  | 2.8599          | 1.0    | 1.0    |
| 2.8858        | 10.0  | 670  | 2.8328          | 1.0    | 1.0    |
| 2.8512        | 11.0  | 737  | 2.5475          | 1.0    | 0.9997 |
| 2.515         | 12.0  | 804  | 1.5878          | 1.0    | 0.5086 |
| 2.515         | 13.0  | 871  | 0.7009          | 0.8586 | 0.1889 |
| 1.3219        | 14.0  | 938  | 0.4050          | 0.2310 | 0.0598 |
| 0.6694        | 15.0  | 1005 | 0.3246          | 0.1755 | 0.0487 |
| 0.6694        | 16.0  | 1072 | 0.2909          | 0.1562 | 0.0439 |
| 0.4976        | 17.0  | 1139 | 0.2679          | 0.1420 | 0.0415 |
| 0.4105        | 18.0  | 1206 | 0.2519          | 0.1292 | 0.0384 |
| 0.4105        | 19.0  | 1273 | 0.2421          | 0.1194 | 0.0366 |
| 0.3865        | 20.0  | 1340 | 0.2325          | 0.1184 | 0.0354 |
| 0.317         | 21.0  | 1407 | 0.2251          | 0.1096 | 0.0341 |
| 0.317         | 22.0  | 1474 | 0.2195          | 0.1092 | 0.0339 |
| 0.2925        | 23.0  | 1541 | 0.2106          | 0.1018 | 0.0320 |
| 0.2721        | 24.0  | 1608 | 0.2072          | 0.0981 | 0.0317 |
| 0.2721        | 25.0  | 1675 | 0.2106          | 0.0981 | 0.0317 |
| 0.2531        | 26.0  | 1742 | 0.2046          | 0.1042 | 0.0330 |
| 0.2634        | 27.0  | 1809 | 0.2071          | 0.1001 | 0.0321 |
| 0.2634        | 28.0  | 1876 | 0.2028          | 0.1042 | 0.0328 |
| 0.2391        | 29.0  | 1943 | 0.1973          | 0.0957 | 0.0308 |
| 0.2232        | 30.0  | 2010 | 0.2017          | 0.0974 | 0.0313 |
| 0.2232        | 31.0  | 2077 | 0.1987          | 0.0974 | 0.0308 |
| 0.2111        | 32.0  | 2144 | 0.1898          | 0.0920 | 0.0298 |
| 0.2121        | 33.0  | 2211 | 0.2006          | 0.0954 | 0.0314 |
| 0.2121        | 34.0  | 2278 | 0.1934          | 0.0920 | 0.0303 |
| 0.1868        | 35.0  | 2345 | 0.1921          | 0.0944 | 0.0306 |
| 0.1869        | 36.0  | 2412 | 0.1884          | 0.0893 | 0.0292 |
| 0.1869        | 37.0  | 2479 | 0.1903          | 0.0866 | 0.0292 |
| 0.1935        | 38.0  | 2546 | 0.1867          | 0.0900 | 0.0294 |
| 0.1957        | 39.0  | 2613 | 0.1874          | 0.0927 | 0.0298 |
| 0.1957        | 40.0  | 2680 | 0.1845          | 0.0923 | 0.0297 |
| 0.1772        | 41.0  | 2747 | 0.1862          | 0.0927 | 0.0298 |
| 0.1748        | 42.0  | 2814 | 0.1894          | 0.0906 | 0.0297 |
| 0.1748        | 43.0  | 2881 | 0.1816          | 0.0933 | 0.0301 |
| 0.1498        | 44.0  | 2948 | 0.1795          | 0.0920 | 0.0296 |
| 0.1606        | 45.0  | 3015 | 0.1867          | 0.0906 | 0.0299 |
| 0.1606        | 46.0  | 3082 | 0.1866          | 0.0886 | 0.0294 |
| 0.1599        | 47.0  | 3149 | 0.1883          | 0.0920 | 0.0300 |
| 0.1487        | 48.0  | 3216 | 0.1802          | 0.0933 | 0.0298 |
| 0.1487        | 49.0  | 3283 | 0.1808          | 0.0937 | 0.0298 |
| 0.148         | 50.0  | 3350 | 0.1824          | 0.0916 | 0.0292 |
| 0.1457        | 51.0  | 3417 | 0.1843          | 0.0893 | 0.0293 |
| 0.1457        | 52.0  | 3484 | 0.1822          | 0.0923 | 0.0293 |
| 0.1472        | 53.0  | 3551 | 0.1766          | 0.0913 | 0.0291 |
| 0.1413        | 54.0  | 3618 | 0.1811          | 0.0933 | 0.0292 |
| 0.1413        | 55.0  | 3685 | 0.1807          | 0.0906 | 0.0291 |
| 0.1357        | 56.0  | 3752 | 0.1808          | 0.0879 | 0.0284 |
| 0.1382        | 57.0  | 3819 | 0.1810          | 0.0933 | 0.0296 |
| 0.1382        | 58.0  | 3886 | 0.1817          | 0.0910 | 0.0287 |
| 0.1371        | 59.0  | 3953 | 0.1844          | 0.0889 | 0.0286 |
| 0.141         | 60.0  | 4020 | 0.1883          | 0.0883 | 0.0284 |
| 0.141         | 61.0  | 4087 | 0.1864          | 0.0930 | 0.0290 |
| 0.147         | 62.0  | 4154 | 0.1861          | 0.0920 | 0.0289 |
| 0.1316        | 63.0  | 4221 | 0.1863          | 0.0950 | 0.0296 |
| 0.1316        | 64.0  | 4288 | 0.1909          | 0.0950 | 0.0302 |
| 0.1329        | 65.0  | 4355 | 0.1880          | 0.0913 | 0.0291 |
| 0.1326        | 66.0  | 4422 | 0.1851          | 0.0930 | 0.0291 |
| 0.1326        | 67.0  | 4489 | 0.1842          | 0.0937 | 0.0292 |
| 0.1345        | 68.0  | 4556 | 0.1856          | 0.0957 | 0.0297 |
| 0.1371        | 69.0  | 4623 | 0.1840          | 0.0927 | 0.0291 |
| 0.1371        | 70.0  | 4690 | 0.1845          | 0.0923 | 0.0292 |
| 0.1325        | 71.0  | 4757 | 0.1806          | 0.0920 | 0.0288 |
| 0.1264        | 72.0  | 4824 | 0.1810          | 0.0923 | 0.0289 |
| 0.1264        | 73.0  | 4891 | 0.1836          | 0.0944 | 0.0295 |


### Framework versions

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