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-03
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-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: 0.1408
- Wer: 0.0770
- Cer: 0.0247

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.3357       | 1.0   | 86   | 3.1566          | 0.9563 | 0.8944 |
| 7.8101        | 2.0   | 172  | 3.0125          | 1.0    | 1.0    |
| 3.7309        | 3.0   | 258  | 2.8713          | 0.9850 | 0.9913 |
| 4.3991        | 4.0   | 344  | 2.8582          | 0.9629 | 0.9566 |
| 4.1408        | 5.0   | 430  | 2.8240          | 0.9717 | 0.9362 |
| 3.734         | 6.0   | 516  | 2.7698          | 0.9520 | 0.8393 |
| 3.3985        | 7.0   | 602  | 2.7666          | 0.9741 | 0.7636 |
| 3.3985        | 8.0   | 688  | 0.6822          | 0.5838 | 0.1672 |
| 1.9243        | 9.0   | 774  | 0.2183          | 0.1343 | 0.0397 |
| 0.5075        | 10.0  | 860  | 0.1937          | 0.1074 | 0.0348 |
| 0.3325        | 11.0  | 946  | 0.1613          | 0.0953 | 0.0305 |
| 0.2617        | 12.0  | 1032 | 0.1571          | 0.0884 | 0.0283 |
| 0.2373        | 13.0  | 1118 | 0.1504          | 0.0851 | 0.0273 |
| 0.2062        | 14.0  | 1204 | 0.1571          | 0.0844 | 0.0267 |
| 0.2062        | 15.0  | 1290 | 0.1472          | 0.0813 | 0.0260 |
| 0.1863        | 16.0  | 1376 | 0.1408          | 0.0770 | 0.0247 |
| 0.1731        | 17.0  | 1462 | 0.1498          | 0.0796 | 0.0254 |
| 0.1431        | 18.0  | 1548 | 0.1543          | 0.0827 | 0.0257 |
| 0.1476        | 19.0  | 1634 | 0.1495          | 0.0834 | 0.0264 |
| 0.1432        | 20.0  | 1720 | 0.1473          | 0.0815 | 0.0252 |
| 0.1263        | 21.0  | 1806 | 0.1573          | 0.0782 | 0.0249 |
| 0.1263        | 22.0  | 1892 | 0.1528          | 0.0765 | 0.0256 |
| 0.1255        | 23.0  | 1978 | 0.1602          | 0.0792 | 0.0261 |
| 0.1151        | 24.0  | 2064 | 0.1614          | 0.0820 | 0.0263 |
| 0.1331        | 25.0  | 2150 | 0.1467          | 0.0792 | 0.0242 |
| 0.1083        | 26.0  | 2236 | 0.1459          | 0.0801 | 0.0248 |
| 0.1072        | 27.0  | 2322 | 0.1616          | 0.0773 | 0.0247 |
| 0.1002        | 28.0  | 2408 | 0.1543          | 0.0751 | 0.0244 |
| 0.1002        | 29.0  | 2494 | 0.1590          | 0.0801 | 0.0249 |
| 0.0995        | 30.0  | 2580 | 0.1642          | 0.0773 | 0.0249 |
| 0.1024        | 31.0  | 2666 | 0.1483          | 0.0792 | 0.0245 |
| 0.0966        | 32.0  | 2752 | 0.1509          | 0.0749 | 0.0239 |
| 0.0947        | 33.0  | 2838 | 0.1546          | 0.0803 | 0.0247 |
| 0.0918        | 34.0  | 2924 | 0.1578          | 0.0770 | 0.0241 |
| 0.0855        | 35.0  | 3010 | 0.1555          | 0.0787 | 0.0249 |
| 0.0855        | 36.0  | 3096 | 0.1552          | 0.0782 | 0.0245 |


### Framework versions

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