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-07
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-07

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: 0.1152
- Wer: 0.0803
- Cer: 0.0225

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.1622       | 1.0   | 67   | 4.2745          | 0.9835 | 0.9326 |
| 5.7807        | 2.0   | 134  | 3.6146          | 0.9890 | 0.9738 |
| 3.5248        | 3.0   | 201  | 2.8795          | 1.0    | 1.0    |
| 3.5248        | 4.0   | 268  | 1.4248          | 0.9997 | 0.4401 |
| 2.1437        | 5.0   | 335  | 0.1879          | 0.1313 | 0.0371 |
| 0.4218        | 6.0   | 402  | 0.1493          | 0.1158 | 0.0297 |
| 0.4218        | 7.0   | 469  | 0.1478          | 0.0934 | 0.0269 |
| 0.29          | 8.0   | 536  | 0.1387          | 0.0879 | 0.0254 |
| 0.2613        | 9.0   | 603  | 0.1240          | 0.0810 | 0.0242 |
| 0.2613        | 10.0  | 670  | 0.1322          | 0.0879 | 0.0257 |
| 0.2155        | 11.0  | 737  | 0.1315          | 0.0882 | 0.0258 |
| 0.1968        | 12.0  | 804  | 0.1238          | 0.0827 | 0.0239 |
| 0.1968        | 13.0  | 871  | 0.1231          | 0.0862 | 0.0242 |
| 0.1878        | 14.0  | 938  | 0.1160          | 0.0917 | 0.0251 |
| 0.1691        | 15.0  | 1005 | 0.1152          | 0.0803 | 0.0225 |
| 0.1691        | 16.0  | 1072 | 0.1348          | 0.0851 | 0.0243 |
| 0.1654        | 17.0  | 1139 | 0.1224          | 0.0807 | 0.0233 |
| 0.1467        | 18.0  | 1206 | 0.1228          | 0.0865 | 0.0245 |
| 0.1467        | 19.0  | 1273 | 0.1231          | 0.0807 | 0.0228 |
| 0.1356        | 20.0  | 1340 | 0.1245          | 0.0807 | 0.0237 |
| 0.1355        | 21.0  | 1407 | 0.1329          | 0.0841 | 0.0247 |
| 0.1355        | 22.0  | 1474 | 0.1294          | 0.0841 | 0.0244 |
| 0.1211        | 23.0  | 1541 | 0.1247          | 0.0782 | 0.0221 |
| 0.1331        | 24.0  | 1608 | 0.1249          | 0.0796 | 0.0228 |
| 0.1331        | 25.0  | 1675 | 0.1257          | 0.0789 | 0.0233 |
| 0.1079        | 26.0  | 1742 | 0.1260          | 0.0903 | 0.0247 |
| 0.1106        | 27.0  | 1809 | 0.1279          | 0.0765 | 0.0222 |
| 0.1106        | 28.0  | 1876 | 0.1295          | 0.0814 | 0.0233 |
| 0.0926        | 29.0  | 1943 | 0.1318          | 0.0831 | 0.0240 |
| 0.1086        | 30.0  | 2010 | 0.1324          | 0.0855 | 0.0237 |
| 0.1086        | 31.0  | 2077 | 0.1285          | 0.0820 | 0.0232 |
| 0.1039        | 32.0  | 2144 | 0.1224          | 0.0814 | 0.0220 |
| 0.0915        | 33.0  | 2211 | 0.1312          | 0.0834 | 0.0231 |
| 0.0915        | 34.0  | 2278 | 0.1290          | 0.0779 | 0.0222 |
| 0.0846        | 35.0  | 2345 | 0.1265          | 0.0789 | 0.0226 |


### Framework versions

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