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-01
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-01

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: 0.1399
- Wer: 0.0805
- Cer: 0.0244

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 30.4316       | 1.0   | 86   | 0.5032          | 0.3767 | 0.0946 |
| 3.5422        | 2.0   | 172  | 0.2198          | 0.1315 | 0.0386 |
| 0.4366        | 3.0   | 258  | 0.1808          | 0.1040 | 0.0312 |
| 0.3345        | 4.0   | 344  | 0.1731          | 0.0955 | 0.0292 |
| 0.2964        | 5.0   | 430  | 0.1753          | 0.1006 | 0.0309 |
| 0.2697        | 6.0   | 516  | 0.1768          | 0.0960 | 0.0306 |
| 0.2356        | 7.0   | 602  | 0.1667          | 0.0916 | 0.0282 |
| 0.2356        | 8.0   | 688  | 0.1692          | 0.0901 | 0.0284 |
| 0.2255        | 9.0   | 774  | 0.1508          | 0.0884 | 0.0275 |
| 0.199         | 10.0  | 860  | 0.1621          | 0.0894 | 0.0282 |
| 0.1853        | 11.0  | 946  | 0.1510          | 0.0876 | 0.0262 |
| 0.1988        | 12.0  | 1032 | 0.1528          | 0.0832 | 0.0258 |
| 0.1788        | 13.0  | 1118 | 0.1569          | 0.0869 | 0.0270 |
| 0.1657        | 14.0  | 1204 | 0.1541          | 0.0889 | 0.0265 |
| 0.1657        | 15.0  | 1290 | 0.1496          | 0.0864 | 0.0264 |
| 0.1668        | 16.0  | 1376 | 0.1448          | 0.0810 | 0.0253 |
| 0.1613        | 17.0  | 1462 | 0.1570          | 0.0884 | 0.0266 |
| 0.1513        | 18.0  | 1548 | 0.1485          | 0.0783 | 0.0246 |
| 0.1402        | 19.0  | 1634 | 0.1486          | 0.0808 | 0.0256 |
| 0.1297        | 20.0  | 1720 | 0.1583          | 0.0798 | 0.0254 |
| 0.1191        | 21.0  | 1806 | 0.1655          | 0.0808 | 0.0252 |
| 0.1191        | 22.0  | 1892 | 0.1657          | 0.0842 | 0.0260 |
| 0.128         | 23.0  | 1978 | 0.1519          | 0.0798 | 0.0243 |
| 0.1136        | 24.0  | 2064 | 0.1399          | 0.0805 | 0.0244 |
| 0.1092        | 25.0  | 2150 | 0.1494          | 0.0803 | 0.0240 |
| 0.1114        | 26.0  | 2236 | 0.1418          | 0.0805 | 0.0248 |
| 0.1039        | 27.0  | 2322 | 0.1527          | 0.0771 | 0.0236 |
| 0.1133        | 28.0  | 2408 | 0.1503          | 0.0808 | 0.0246 |
| 0.1133        | 29.0  | 2494 | 0.1675          | 0.0800 | 0.0249 |
| 0.0939        | 30.0  | 2580 | 0.1696          | 0.0837 | 0.0254 |
| 0.0964        | 31.0  | 2666 | 0.1608          | 0.0823 | 0.0251 |
| 0.0959        | 32.0  | 2752 | 0.1577          | 0.0796 | 0.0253 |
| 0.0987        | 33.0  | 2838 | 0.1566          | 0.0798 | 0.0247 |
| 0.0909        | 34.0  | 2924 | 0.1620          | 0.0813 | 0.0248 |
| 0.0982        | 35.0  | 3010 | 0.1634          | 0.0798 | 0.0243 |
| 0.0982        | 36.0  | 3096 | 0.1541          | 0.0742 | 0.0232 |
| 0.0937        | 37.0  | 3182 | 0.1655          | 0.0769 | 0.0236 |
| 0.0836        | 38.0  | 3268 | 0.1718          | 0.0791 | 0.0244 |
| 0.0752        | 39.0  | 3354 | 0.1667          | 0.0793 | 0.0246 |
| 0.0869        | 40.0  | 3440 | 0.1620          | 0.0774 | 0.0244 |
| 0.077         | 41.0  | 3526 | 0.1776          | 0.0803 | 0.0252 |
| 0.0727        | 42.0  | 3612 | 0.1744          | 0.0798 | 0.0250 |
| 0.0727        | 43.0  | 3698 | 0.1754          | 0.0729 | 0.0237 |
| 0.0745        | 44.0  | 3784 | 0.1655          | 0.0803 | 0.0244 |


### Framework versions

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