---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-04
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-04

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: 0.1832
- Wer: 0.0896
- Cer: 0.0286

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.4874       | 1.0   | 86   | 3.3048          | 1.0    | 1.0    |
| 7.6481        | 2.0   | 172  | 2.9770          | 1.0    | 1.0    |
| 3.0297        | 3.0   | 258  | 2.9361          | 1.0    | 1.0    |
| 2.9192        | 4.0   | 344  | 2.9206          | 1.0    | 1.0    |
| 2.8826        | 5.0   | 430  | 2.6372          | 0.9990 | 0.9993 |
| 2.3512        | 6.0   | 516  | 0.8687          | 0.4358 | 0.1113 |
| 1.0373        | 7.0   | 602  | 0.5095          | 0.2419 | 0.0665 |
| 1.0373        | 8.0   | 688  | 0.4001          | 0.2101 | 0.0584 |
| 0.6758        | 9.0   | 774  | 0.3354          | 0.1799 | 0.0502 |
| 0.5667        | 10.0  | 860  | 0.2962          | 0.1617 | 0.0468 |
| 0.4908        | 11.0  | 946  | 0.2820          | 0.1471 | 0.0430 |
| 0.4084        | 12.0  | 1032 | 0.2581          | 0.1351 | 0.0399 |
| 0.3728        | 13.0  | 1118 | 0.2444          | 0.1230 | 0.0374 |
| 0.3577        | 14.0  | 1204 | 0.2408          | 0.1144 | 0.0355 |
| 0.3577        | 15.0  | 1290 | 0.2353          | 0.1100 | 0.0340 |
| 0.3237        | 16.0  | 1376 | 0.2227          | 0.1036 | 0.0332 |
| 0.3043        | 17.0  | 1462 | 0.2241          | 0.1004 | 0.0322 |
| 0.2876        | 18.0  | 1548 | 0.2260          | 0.1048 | 0.0329 |
| 0.2842        | 19.0  | 1634 | 0.2086          | 0.1070 | 0.0325 |
| 0.269         | 20.0  | 1720 | 0.2156          | 0.1006 | 0.0324 |
| 0.2396        | 21.0  | 1806 | 0.2065          | 0.0952 | 0.0307 |
| 0.2396        | 22.0  | 1892 | 0.2144          | 0.0960 | 0.0312 |
| 0.2411        | 23.0  | 1978 | 0.2018          | 0.0933 | 0.0307 |
| 0.2357        | 24.0  | 2064 | 0.2055          | 0.0940 | 0.0305 |
| 0.2268        | 25.0  | 2150 | 0.2099          | 0.0928 | 0.0307 |
| 0.2053        | 26.0  | 2236 | 0.2044          | 0.0933 | 0.0302 |
| 0.2188        | 27.0  | 2322 | 0.2037          | 0.0933 | 0.0301 |
| 0.2152        | 28.0  | 2408 | 0.2068          | 0.0933 | 0.0298 |
| 0.2152        | 29.0  | 2494 | 0.2044          | 0.0898 | 0.0283 |
| 0.1998        | 30.0  | 2580 | 0.2039          | 0.0888 | 0.0294 |
| 0.1934        | 31.0  | 2666 | 0.1965          | 0.0915 | 0.0296 |
| 0.19          | 32.0  | 2752 | 0.1994          | 0.0908 | 0.0291 |
| 0.2108        | 33.0  | 2838 | 0.2026          | 0.0888 | 0.0292 |
| 0.1922        | 34.0  | 2924 | 0.1957          | 0.0906 | 0.0292 |
| 0.1827        | 35.0  | 3010 | 0.1935          | 0.0893 | 0.0287 |
| 0.1827        | 36.0  | 3096 | 0.1933          | 0.0906 | 0.0295 |
| 0.1848        | 37.0  | 3182 | 0.1999          | 0.0883 | 0.0287 |
| 0.1807        | 38.0  | 3268 | 0.1949          | 0.0881 | 0.0287 |
| 0.1695        | 39.0  | 3354 | 0.1968          | 0.0906 | 0.0295 |
| 0.1764        | 40.0  | 3440 | 0.1894          | 0.0864 | 0.0284 |
| 0.1812        | 41.0  | 3526 | 0.1932          | 0.0871 | 0.0286 |
| 0.1566        | 42.0  | 3612 | 0.1889          | 0.0869 | 0.0281 |
| 0.1566        | 43.0  | 3698 | 0.1965          | 0.0864 | 0.0282 |
| 0.161         | 44.0  | 3784 | 0.1832          | 0.0896 | 0.0286 |
| 0.167         | 45.0  | 3870 | 0.1968          | 0.0886 | 0.0282 |
| 0.1556        | 46.0  | 3956 | 0.1835          | 0.0881 | 0.0283 |
| 0.157         | 47.0  | 4042 | 0.1912          | 0.0864 | 0.0279 |
| 0.1588        | 48.0  | 4128 | 0.1926          | 0.0883 | 0.0279 |
| 0.1543        | 49.0  | 4214 | 0.1961          | 0.0869 | 0.0282 |
| 0.1528        | 50.0  | 4300 | 0.1959          | 0.0886 | 0.0286 |
| 0.1528        | 51.0  | 4386 | 0.1938          | 0.0869 | 0.0277 |
| 0.1477        | 52.0  | 4472 | 0.1984          | 0.0839 | 0.0272 |
| 0.1533        | 53.0  | 4558 | 0.1969          | 0.0864 | 0.0274 |
| 0.1351        | 54.0  | 4644 | 0.1983          | 0.0856 | 0.0275 |
| 0.1468        | 55.0  | 4730 | 0.1970          | 0.0834 | 0.0272 |
| 0.1406        | 56.0  | 4816 | 0.1940          | 0.0817 | 0.0270 |
| 0.1412        | 57.0  | 4902 | 0.1894          | 0.0859 | 0.0277 |
| 0.1412        | 58.0  | 4988 | 0.1929          | 0.0856 | 0.0275 |
| 0.1435        | 59.0  | 5074 | 0.1977          | 0.0859 | 0.0278 |
| 0.1389        | 60.0  | 5160 | 0.1986          | 0.0849 | 0.0277 |
| 0.1366        | 61.0  | 5246 | 0.1977          | 0.0856 | 0.0272 |
| 0.1367        | 62.0  | 5332 | 0.1948          | 0.0851 | 0.0275 |
| 0.1268        | 63.0  | 5418 | 0.1947          | 0.0856 | 0.0275 |
| 0.1441        | 64.0  | 5504 | 0.1956          | 0.0856 | 0.0277 |


### Framework versions

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