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-xlsr-1b-mecita-portuguese-all-02
  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-xlsr-1b-mecita-portuguese-all-02

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-xls-r-1b-portuguese](https://huggingface.co/jonatasgrosman/wav2vec2-xls-r-1b-portuguese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1771
- Wer: 0.0905
- Cer: 0.0274

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 26.1766       | 1.0   | 86   | 0.4520          | 0.2465 | 0.0709 |
| 3.4072        | 2.0   | 172  | 0.2510          | 0.1273 | 0.0399 |
| 0.4643        | 3.0   | 258  | 0.2151          | 0.1095 | 0.0343 |
| 0.3367        | 4.0   | 344  | 0.2069          | 0.1083 | 0.0332 |
| 0.3088        | 5.0   | 430  | 0.2011          | 0.1044 | 0.0319 |
| 0.2696        | 6.0   | 516  | 0.1893          | 0.0985 | 0.0303 |
| 0.2496        | 7.0   | 602  | 0.1841          | 0.0975 | 0.0301 |
| 0.2496        | 8.0   | 688  | 0.1937          | 0.0941 | 0.0296 |
| 0.2787        | 9.0   | 774  | 0.1858          | 0.0902 | 0.0290 |
| 0.2032        | 10.0  | 860  | 0.1936          | 0.0875 | 0.0285 |
| 0.1938        | 11.0  | 946  | 0.1858          | 0.0873 | 0.0273 |
| 0.1836        | 12.0  | 1032 | 0.1839          | 0.0890 | 0.0279 |
| 0.1696        | 13.0  | 1118 | 0.1866          | 0.0883 | 0.0284 |
| 0.1697        | 14.0  | 1204 | 0.1862          | 0.0885 | 0.0275 |
| 0.1697        | 15.0  | 1290 | 0.1889          | 0.0941 | 0.0291 |
| 0.1767        | 16.0  | 1376 | 0.1846          | 0.0917 | 0.0278 |
| 0.1713        | 17.0  | 1462 | 0.1899          | 0.0888 | 0.0275 |
| 0.1548        | 18.0  | 1548 | 0.1924          | 0.0888 | 0.0280 |
| 0.144         | 19.0  | 1634 | 0.1824          | 0.0885 | 0.0271 |
| 0.1363        | 20.0  | 1720 | 0.1771          | 0.0905 | 0.0274 |
| 0.1227        | 21.0  | 1806 | 0.1845          | 0.0839 | 0.0260 |
| 0.1227        | 22.0  | 1892 | 0.1871          | 0.0841 | 0.0264 |
| 0.1177        | 23.0  | 1978 | 0.1833          | 0.0888 | 0.0276 |
| 0.1229        | 24.0  | 2064 | 0.1914          | 0.0844 | 0.0261 |
| 0.1149        | 25.0  | 2150 | 0.1930          | 0.0846 | 0.0265 |
| 0.1112        | 26.0  | 2236 | 0.2113          | 0.0853 | 0.0272 |
| 0.1055        | 27.0  | 2322 | 0.1922          | 0.0863 | 0.0268 |
| 0.1082        | 28.0  | 2408 | 0.1918          | 0.0839 | 0.0266 |
| 0.1082        | 29.0  | 2494 | 0.1863          | 0.0858 | 0.0270 |
| 0.1054        | 30.0  | 2580 | 0.2062          | 0.0858 | 0.0275 |
| 0.0879        | 31.0  | 2666 | 0.1893          | 0.0846 | 0.0270 |
| 0.0951        | 32.0  | 2752 | 0.1939          | 0.0912 | 0.0274 |
| 0.1005        | 33.0  | 2838 | 0.1980          | 0.0832 | 0.0268 |
| 0.0923        | 34.0  | 2924 | 0.2058          | 0.0868 | 0.0274 |
| 0.0873        | 35.0  | 3010 | 0.1999          | 0.0829 | 0.0264 |
| 0.0873        | 36.0  | 3096 | 0.2027          | 0.0858 | 0.0272 |
| 0.0997        | 37.0  | 3182 | 0.2029          | 0.0836 | 0.0268 |
| 0.0898        | 38.0  | 3268 | 0.1940          | 0.0834 | 0.0264 |
| 0.0863        | 39.0  | 3354 | 0.2077          | 0.0844 | 0.0268 |
| 0.1018        | 40.0  | 3440 | 0.2058          | 0.0851 | 0.0273 |


### Framework versions

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