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-03
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-03

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: 0.1307
- Wer: 0.0783
- Cer: 0.0231

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 21.675        | 1.0   | 67   | 4.4178          | 0.9636 | 0.9162 |
| 6.0023        | 2.0   | 134  | 3.9535          | 0.9818 | 0.9783 |
| 4.2873        | 3.0   | 201  | 3.7663          | 0.9719 | 0.9834 |
| 4.2873        | 4.0   | 268  | 3.0601          | 0.9881 | 0.9680 |
| 3.5535        | 5.0   | 335  | 0.4943          | 0.5511 | 0.1220 |
| 1.0258        | 6.0   | 402  | 0.1872          | 0.1150 | 0.0329 |
| 1.0258        | 7.0   | 469  | 0.1534          | 0.0998 | 0.0283 |
| 0.3109        | 8.0   | 536  | 0.1406          | 0.0899 | 0.0267 |
| 0.2534        | 9.0   | 603  | 0.1432          | 0.0774 | 0.0237 |
| 0.2534        | 10.0  | 670  | 0.1325          | 0.08   | 0.0237 |
| 0.2109        | 11.0  | 737  | 0.1342          | 0.0803 | 0.0233 |
| 0.1998        | 12.0  | 804  | 0.1322          | 0.0856 | 0.0245 |
| 0.1998        | 13.0  | 871  | 0.1355          | 0.0807 | 0.0233 |
| 0.1696        | 14.0  | 938  | 0.1343          | 0.0754 | 0.0224 |
| 0.1875        | 15.0  | 1005 | 0.1320          | 0.0747 | 0.0232 |
| 0.1875        | 16.0  | 1072 | 0.1361          | 0.0737 | 0.0226 |
| 0.1501        | 17.0  | 1139 | 0.1307          | 0.0783 | 0.0231 |
| 0.1433        | 18.0  | 1206 | 0.1410          | 0.0790 | 0.0242 |
| 0.1433        | 19.0  | 1273 | 0.1412          | 0.0840 | 0.0246 |
| 0.1336        | 20.0  | 1340 | 0.1320          | 0.0740 | 0.0230 |
| 0.1443        | 21.0  | 1407 | 0.1308          | 0.0754 | 0.0228 |
| 0.1443        | 22.0  | 1474 | 0.1366          | 0.0750 | 0.0224 |
| 0.1253        | 23.0  | 1541 | 0.1396          | 0.0793 | 0.0237 |
| 0.1145        | 24.0  | 1608 | 0.1317          | 0.0754 | 0.0230 |
| 0.1145        | 25.0  | 1675 | 0.1346          | 0.0790 | 0.0241 |
| 0.1071        | 26.0  | 1742 | 0.1343          | 0.0724 | 0.0232 |
| 0.0989        | 27.0  | 1809 | 0.1343          | 0.0750 | 0.0232 |
| 0.0989        | 28.0  | 1876 | 0.1332          | 0.0744 | 0.0228 |
| 0.0982        | 29.0  | 1943 | 0.1348          | 0.0714 | 0.0216 |
| 0.0934        | 30.0  | 2010 | 0.1351          | 0.0698 | 0.0219 |
| 0.0934        | 31.0  | 2077 | 0.1349          | 0.0740 | 0.0231 |
| 0.088         | 32.0  | 2144 | 0.1341          | 0.0691 | 0.0225 |
| 0.086         | 33.0  | 2211 | 0.1336          | 0.0731 | 0.0227 |
| 0.086         | 34.0  | 2278 | 0.1398          | 0.0757 | 0.0240 |
| 0.0907        | 35.0  | 2345 | 0.1494          | 0.0714 | 0.0225 |
| 0.0974        | 36.0  | 2412 | 0.1455          | 0.0754 | 0.0232 |
| 0.0974        | 37.0  | 2479 | 0.1436          | 0.0724 | 0.0237 |


### Framework versions

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