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-06
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-06

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: 0.1243
- Wer: 0.0823
- Cer: 0.0243

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 24.9822       | 1.0   | 67   | 3.8001          | 0.9668 | 0.8169 |
| 6.3192        | 2.0   | 134  | 3.2618          | 0.9794 | 0.9773 |
| 4.1532        | 3.0   | 201  | 3.2294          | 0.9770 | 0.9800 |
| 4.1532        | 4.0   | 268  | 2.8781          | 0.9946 | 0.9900 |
| 3.3713        | 5.0   | 335  | 0.2855          | 0.1882 | 0.0521 |
| 0.6517        | 6.0   | 402  | 0.1736          | 0.1131 | 0.0330 |
| 0.6517        | 7.0   | 469  | 0.1476          | 0.1032 | 0.0300 |
| 0.318         | 8.0   | 536  | 0.1320          | 0.0880 | 0.0254 |
| 0.2177        | 9.0   | 603  | 0.1313          | 0.0856 | 0.0252 |
| 0.2177        | 10.0  | 670  | 0.1375          | 0.0897 | 0.0268 |
| 0.2075        | 11.0  | 737  | 0.1494          | 0.0873 | 0.0265 |
| 0.191         | 12.0  | 804  | 0.1243          | 0.0823 | 0.0243 |
| 0.191         | 13.0  | 871  | 0.1267          | 0.0816 | 0.0245 |
| 0.1701        | 14.0  | 938  | 0.1371          | 0.0812 | 0.0246 |
| 0.17          | 15.0  | 1005 | 0.1413          | 0.0799 | 0.0253 |
| 0.17          | 16.0  | 1072 | 0.1368          | 0.0812 | 0.0247 |
| 0.1462        | 17.0  | 1139 | 0.1353          | 0.0850 | 0.0257 |
| 0.1571        | 18.0  | 1206 | 0.1413          | 0.0880 | 0.0259 |
| 0.1571        | 19.0  | 1273 | 0.1362          | 0.0785 | 0.0242 |
| 0.1275        | 20.0  | 1340 | 0.1293          | 0.0765 | 0.0230 |
| 0.1233        | 21.0  | 1407 | 0.1318          | 0.0782 | 0.0243 |
| 0.1233        | 22.0  | 1474 | 0.1392          | 0.0853 | 0.0250 |
| 0.1269        | 23.0  | 1541 | 0.1344          | 0.0853 | 0.0254 |
| 0.133         | 24.0  | 1608 | 0.1366          | 0.0812 | 0.0249 |
| 0.133         | 25.0  | 1675 | 0.1249          | 0.0779 | 0.0238 |
| 0.1182        | 26.0  | 1742 | 0.1394          | 0.0840 | 0.0254 |
| 0.1221        | 27.0  | 1809 | 0.1415          | 0.0843 | 0.0259 |
| 0.1221        | 28.0  | 1876 | 0.1437          | 0.0812 | 0.0253 |
| 0.1061        | 29.0  | 1943 | 0.1461          | 0.0840 | 0.0260 |
| 0.1115        | 30.0  | 2010 | 0.1399          | 0.0829 | 0.0249 |
| 0.1115        | 31.0  | 2077 | 0.1456          | 0.0758 | 0.0239 |
| 0.091         | 32.0  | 2144 | 0.1426          | 0.0785 | 0.0241 |


### Framework versions

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