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-05
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-05

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: 0.1086
- Wer: 0.0735
- Cer: 0.0203

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.1639       | 1.0   | 67   | 5.3450          | 0.9555 | 0.8892 |
| 6.8724        | 2.0   | 134  | 2.9255          | 0.9960 | 0.9970 |
| 3.2578        | 3.0   | 201  | 2.5391          | 0.9960 | 0.9826 |
| 3.2578        | 4.0   | 268  | 0.1894          | 0.1367 | 0.0365 |
| 0.9083        | 5.0   | 335  | 0.1536          | 0.0985 | 0.0278 |
| 0.3078        | 6.0   | 402  | 0.1411          | 0.0810 | 0.0242 |
| 0.3078        | 7.0   | 469  | 0.1160          | 0.0784 | 0.0219 |
| 0.2553        | 8.0   | 536  | 0.1162          | 0.0840 | 0.0228 |
| 0.2452        | 9.0   | 603  | 0.1181          | 0.0794 | 0.0226 |
| 0.2452        | 10.0  | 670  | 0.1163          | 0.0754 | 0.0213 |
| 0.2157        | 11.0  | 737  | 0.1209          | 0.0721 | 0.0212 |
| 0.1966        | 12.0  | 804  | 0.1203          | 0.0738 | 0.0210 |
| 0.1966        | 13.0  | 871  | 0.1220          | 0.0774 | 0.0214 |
| 0.1695        | 14.0  | 938  | 0.1169          | 0.0777 | 0.0213 |
| 0.1703        | 15.0  | 1005 | 0.1218          | 0.0761 | 0.0215 |
| 0.1703        | 16.0  | 1072 | 0.1268          | 0.0764 | 0.0213 |
| 0.1391        | 17.0  | 1139 | 0.1086          | 0.0735 | 0.0203 |
| 0.1448        | 18.0  | 1206 | 0.1160          | 0.0715 | 0.0203 |
| 0.1448        | 19.0  | 1273 | 0.1187          | 0.0708 | 0.0201 |
| 0.1448        | 20.0  | 1340 | 0.1194          | 0.0695 | 0.0198 |
| 0.1304        | 21.0  | 1407 | 0.1221          | 0.0721 | 0.0200 |
| 0.1304        | 22.0  | 1474 | 0.1268          | 0.0711 | 0.0196 |
| 0.1309        | 23.0  | 1541 | 0.1216          | 0.0711 | 0.0204 |
| 0.1179        | 24.0  | 1608 | 0.1361          | 0.0725 | 0.0203 |
| 0.1179        | 25.0  | 1675 | 0.1228          | 0.0725 | 0.0202 |
| 0.119         | 26.0  | 1742 | 0.1175          | 0.0705 | 0.0198 |
| 0.0985        | 27.0  | 1809 | 0.1306          | 0.0695 | 0.0202 |
| 0.0985        | 28.0  | 1876 | 0.1236          | 0.0711 | 0.0195 |
| 0.1016        | 29.0  | 1943 | 0.1191          | 0.0688 | 0.0197 |
| 0.0907        | 30.0  | 2010 | 0.1233          | 0.0695 | 0.0195 |
| 0.0907        | 31.0  | 2077 | 0.1180          | 0.0698 | 0.0188 |
| 0.0957        | 32.0  | 2144 | 0.1311          | 0.0715 | 0.0203 |
| 0.0973        | 33.0  | 2211 | 0.1319          | 0.0659 | 0.0195 |
| 0.0973        | 34.0  | 2278 | 0.1260          | 0.0705 | 0.0199 |
| 0.0938        | 35.0  | 2345 | 0.1263          | 0.0662 | 0.0192 |
| 0.0933        | 36.0  | 2412 | 0.1216          | 0.0682 | 0.0193 |
| 0.0933        | 37.0  | 2479 | 0.1208          | 0.0675 | 0.0202 |


### Framework versions

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