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-10
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-10

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: 0.1813
- Wer: 0.0938
- Cer: 0.0330

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.3451       | 1.0   | 86   | 0.9640          | 0.5666 | 0.1819 |
| 3.9749        | 2.0   | 172  | 0.2877          | 0.1346 | 0.0469 |
| 0.4996        | 3.0   | 258  | 0.2273          | 0.1172 | 0.0421 |
| 0.3552        | 4.0   | 344  | 0.2042          | 0.1107 | 0.0393 |
| 0.2886        | 5.0   | 430  | 0.2033          | 0.1091 | 0.0391 |
| 0.2699        | 6.0   | 516  | 0.1935          | 0.1024 | 0.0377 |
| 0.2384        | 7.0   | 602  | 0.2023          | 0.1074 | 0.0383 |
| 0.2384        | 8.0   | 688  | 0.1939          | 0.0964 | 0.0352 |
| 0.212         | 9.0   | 774  | 0.1929          | 0.1029 | 0.0362 |
| 0.1951        | 10.0  | 860  | 0.1957          | 0.1026 | 0.0374 |
| 0.1637        | 11.0  | 946  | 0.2004          | 0.0971 | 0.0355 |
| 0.1877        | 12.0  | 1032 | 0.1847          | 0.0943 | 0.0335 |
| 0.1725        | 13.0  | 1118 | 0.1813          | 0.0938 | 0.0330 |
| 0.1405        | 14.0  | 1204 | 0.1911          | 0.0940 | 0.0336 |
| 0.1405        | 15.0  | 1290 | 0.1926          | 0.0959 | 0.0345 |
| 0.163         | 16.0  | 1376 | 0.1868          | 0.0959 | 0.0353 |
| 0.1355        | 17.0  | 1462 | 0.1965          | 0.0957 | 0.0351 |
| 0.1408        | 18.0  | 1548 | 0.1970          | 0.1021 | 0.0361 |
| 0.1276        | 19.0  | 1634 | 0.2001          | 0.0938 | 0.0349 |
| 0.1392        | 20.0  | 1720 | 0.1935          | 0.0909 | 0.0338 |
| 0.117         | 21.0  | 1806 | 0.1943          | 0.0976 | 0.0355 |
| 0.117         | 22.0  | 1892 | 0.2038          | 0.0995 | 0.0367 |
| 0.1369        | 23.0  | 1978 | 0.1898          | 0.0964 | 0.0341 |
| 0.1168        | 24.0  | 2064 | 0.1883          | 0.0919 | 0.0333 |
| 0.1128        | 25.0  | 2150 | 0.1822          | 0.0897 | 0.0324 |
| 0.1193        | 26.0  | 2236 | 0.1852          | 0.0931 | 0.0324 |
| 0.1023        | 27.0  | 2322 | 0.1934          | 0.0981 | 0.0329 |
| 0.1127        | 28.0  | 2408 | 0.1967          | 0.0885 | 0.0319 |
| 0.1127        | 29.0  | 2494 | 0.1878          | 0.0859 | 0.0322 |
| 0.0896        | 30.0  | 2580 | 0.1898          | 0.0897 | 0.0328 |
| 0.0917        | 31.0  | 2666 | 0.1935          | 0.0921 | 0.0331 |
| 0.0936        | 32.0  | 2752 | 0.1985          | 0.0916 | 0.0332 |
| 0.1012        | 33.0  | 2838 | 0.2010          | 0.0931 | 0.0336 |


### Framework versions

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