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-clean-02
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-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: 0.1154
- Wer: 0.0813
- Cer: 0.0226

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 24.2792       | 1.0   | 67   | 2.8011          | 0.9997 | 0.9999 |
| 4.1558        | 2.0   | 134  | 0.2045          | 0.1477 | 0.0381 |
| 0.4516        | 3.0   | 201  | 0.1470          | 0.1058 | 0.0277 |
| 0.4516        | 4.0   | 268  | 0.1538          | 0.1058 | 0.0282 |
| 0.3013        | 5.0   | 335  | 0.1466          | 0.0941 | 0.0252 |
| 0.2386        | 6.0   | 402  | 0.1402          | 0.0930 | 0.0259 |
| 0.2386        | 7.0   | 469  | 0.1284          | 0.0886 | 0.0253 |
| 0.2219        | 8.0   | 536  | 0.1226          | 0.0896 | 0.0247 |
| 0.2165        | 9.0   | 603  | 0.1283          | 0.0868 | 0.0243 |
| 0.2165        | 10.0  | 670  | 0.1223          | 0.0834 | 0.0230 |
| 0.186         | 11.0  | 737  | 0.1182          | 0.0872 | 0.0239 |
| 0.1749        | 12.0  | 804  | 0.1303          | 0.0879 | 0.0242 |
| 0.1749        | 13.0  | 871  | 0.1265          | 0.0906 | 0.0249 |
| 0.2178        | 14.0  | 938  | 0.1213          | 0.0809 | 0.0235 |
| 0.1548        | 15.0  | 1005 | 0.1231          | 0.0830 | 0.0228 |
| 0.1548        | 16.0  | 1072 | 0.1193          | 0.0816 | 0.0226 |
| 0.1456        | 17.0  | 1139 | 0.1154          | 0.0813 | 0.0226 |
| 0.1345        | 18.0  | 1206 | 0.1346          | 0.0820 | 0.0232 |
| 0.1345        | 19.0  | 1273 | 0.1316          | 0.0816 | 0.0232 |
| 0.1339        | 20.0  | 1340 | 0.1206          | 0.0802 | 0.0224 |
| 0.1236        | 21.0  | 1407 | 0.1363          | 0.0830 | 0.0232 |
| 0.1236        | 22.0  | 1474 | 0.1221          | 0.0733 | 0.0216 |
| 0.1182        | 23.0  | 1541 | 0.1287          | 0.0778 | 0.0224 |
| 0.1185        | 24.0  | 1608 | 0.1229          | 0.0796 | 0.0235 |
| 0.1185        | 25.0  | 1675 | 0.1332          | 0.0768 | 0.0222 |
| 0.135         | 26.0  | 1742 | 0.1259          | 0.0792 | 0.0224 |
| 0.1091        | 27.0  | 1809 | 0.1298          | 0.0809 | 0.0230 |
| 0.1091        | 28.0  | 1876 | 0.1327          | 0.0778 | 0.0219 |
| 0.1045        | 29.0  | 1943 | 0.1322          | 0.0799 | 0.0230 |
| 0.0943        | 30.0  | 2010 | 0.1217          | 0.0799 | 0.0229 |
| 0.0943        | 31.0  | 2077 | 0.1383          | 0.0827 | 0.0237 |
| 0.1003        | 32.0  | 2144 | 0.1427          | 0.0820 | 0.0232 |
| 0.11          | 33.0  | 2211 | 0.1441          | 0.0799 | 0.0229 |
| 0.11          | 34.0  | 2278 | 0.1268          | 0.0764 | 0.0214 |
| 0.0876        | 35.0  | 2345 | 0.1393          | 0.0820 | 0.0233 |
| 0.0818        | 36.0  | 2412 | 0.1308          | 0.0758 | 0.0210 |
| 0.0818        | 37.0  | 2479 | 0.1238          | 0.0830 | 0.0223 |


### Framework versions

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