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-09
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-09

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: 0.1091
- Wer: 0.0715
- Cer: 0.0201

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.1893       | 1.0   | 67   | 5.5870          | 0.9891 | 0.9135 |
| 8.4096        | 2.0   | 134  | 3.3389          | 0.9888 | 0.9614 |
| 4.6285        | 3.0   | 201  | 3.5010          | 0.9713 | 0.9829 |
| 4.6285        | 4.0   | 268  | 3.1012          | 0.9746 | 0.9824 |
| 4.1632        | 5.0   | 335  | 3.0531          | 0.9766 | 0.9801 |
| 3.6744        | 6.0   | 402  | 3.0343          | 0.9868 | 0.9739 |
| 3.6744        | 7.0   | 469  | 2.8810          | 1.0    | 1.0    |
| 3.0111        | 8.0   | 536  | 2.4821          | 0.9970 | 0.9612 |
| 2.0541        | 9.0   | 603  | 0.4203          | 0.5659 | 0.1206 |
| 2.0541        | 10.0  | 670  | 0.1569          | 0.1107 | 0.0288 |
| 0.4608        | 11.0  | 737  | 0.1331          | 0.0975 | 0.0263 |
| 0.2892        | 12.0  | 804  | 0.1344          | 0.0955 | 0.0254 |
| 0.2892        | 13.0  | 871  | 0.1242          | 0.0797 | 0.0226 |
| 0.2182        | 14.0  | 938  | 0.1217          | 0.0837 | 0.0240 |
| 0.2017        | 15.0  | 1005 | 0.1147          | 0.0728 | 0.0208 |
| 0.2017        | 16.0  | 1072 | 0.1206          | 0.0725 | 0.0216 |
| 0.1666        | 17.0  | 1139 | 0.1155          | 0.0744 | 0.0215 |
| 0.169         | 18.0  | 1206 | 0.1175          | 0.0744 | 0.0213 |
| 0.169         | 19.0  | 1273 | 0.1187          | 0.0787 | 0.0218 |
| 0.1678        | 20.0  | 1340 | 0.1211          | 0.0744 | 0.0216 |
| 0.148         | 21.0  | 1407 | 0.1153          | 0.0715 | 0.0205 |
| 0.148         | 22.0  | 1474 | 0.1164          | 0.0728 | 0.0213 |
| 0.1487        | 23.0  | 1541 | 0.1091          | 0.0715 | 0.0201 |
| 0.138         | 24.0  | 1608 | 0.1204          | 0.0705 | 0.0202 |
| 0.138         | 25.0  | 1675 | 0.1114          | 0.0698 | 0.0201 |
| 0.1251        | 26.0  | 1742 | 0.1180          | 0.0688 | 0.0202 |
| 0.1056        | 27.0  | 1809 | 0.1188          | 0.0675 | 0.0199 |
| 0.1056        | 28.0  | 1876 | 0.1123          | 0.0652 | 0.0188 |
| 0.1107        | 29.0  | 1943 | 0.1226          | 0.0728 | 0.0215 |
| 0.0972        | 30.0  | 2010 | 0.1221          | 0.0705 | 0.0205 |
| 0.0972        | 31.0  | 2077 | 0.1226          | 0.0702 | 0.0207 |
| 0.1032        | 32.0  | 2144 | 0.1159          | 0.0669 | 0.0195 |
| 0.1038        | 33.0  | 2211 | 0.1205          | 0.0711 | 0.0204 |
| 0.1038        | 34.0  | 2278 | 0.1191          | 0.0685 | 0.0192 |
| 0.1027        | 35.0  | 2345 | 0.1170          | 0.0688 | 0.0198 |
| 0.1           | 36.0  | 2412 | 0.1189          | 0.0659 | 0.0198 |
| 0.1           | 37.0  | 2479 | 0.1102          | 0.0649 | 0.0187 |
| 0.0989        | 38.0  | 2546 | 0.1150          | 0.0718 | 0.0206 |
| 0.089         | 39.0  | 2613 | 0.1202          | 0.0682 | 0.0195 |
| 0.089         | 40.0  | 2680 | 0.1168          | 0.0669 | 0.0194 |
| 0.0807        | 41.0  | 2747 | 0.1161          | 0.0669 | 0.0190 |
| 0.0812        | 42.0  | 2814 | 0.1208          | 0.0715 | 0.0204 |
| 0.0812        | 43.0  | 2881 | 0.1260          | 0.0629 | 0.0193 |


### Framework versions

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