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-08
  results: []
---

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# wav2vec2-xlsr-1b-mecita-portuguese-all-08

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: 0.1559
- Wer: 0.0812
- Cer: 0.0233

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 29.1451       | 1.0   | 86   | 0.4184          | 0.2658 | 0.0705 |
| 3.4145        | 2.0   | 172  | 0.2155          | 0.1215 | 0.0344 |
| 0.4615        | 3.0   | 258  | 0.1863          | 0.1133 | 0.0323 |
| 0.3181        | 4.0   | 344  | 0.1977          | 0.0915 | 0.0272 |
| 0.2988        | 5.0   | 430  | 0.1800          | 0.0887 | 0.0267 |
| 0.2469        | 6.0   | 516  | 0.1644          | 0.0917 | 0.0265 |
| 0.2295        | 7.0   | 602  | 0.1740          | 0.0891 | 0.0256 |
| 0.2295        | 8.0   | 688  | 0.1746          | 0.0866 | 0.0244 |
| 0.2247        | 9.0   | 774  | 0.1792          | 0.0828 | 0.0249 |
| 0.1997        | 10.0  | 860  | 0.1875          | 0.0856 | 0.0239 |
| 0.1999        | 11.0  | 946  | 0.2118          | 0.0833 | 0.0243 |
| 0.1821        | 12.0  | 1032 | 0.1777          | 0.0789 | 0.0236 |
| 0.1824        | 13.0  | 1118 | 0.2841          | 0.0794 | 0.0246 |
| 0.1737        | 14.0  | 1204 | 0.1559          | 0.0812 | 0.0233 |
| 0.1737        | 15.0  | 1290 | 0.1591          | 0.0773 | 0.0223 |
| 0.158         | 16.0  | 1376 | 0.1767          | 0.0770 | 0.0224 |
| 0.1508        | 17.0  | 1462 | 0.1606          | 0.0766 | 0.0217 |
| 0.1485        | 18.0  | 1548 | 0.1787          | 0.0787 | 0.0237 |
| 0.1606        | 19.0  | 1634 | 0.1766          | 0.0808 | 0.0243 |
| 0.1271        | 20.0  | 1720 | 0.1770          | 0.0780 | 0.0233 |
| 0.1251        | 21.0  | 1806 | 0.1648          | 0.0749 | 0.0223 |
| 0.1251        | 22.0  | 1892 | 0.1918          | 0.0707 | 0.0222 |
| 0.1343        | 23.0  | 1978 | 0.1740          | 0.0768 | 0.0228 |
| 0.1269        | 24.0  | 2064 | 0.1714          | 0.0796 | 0.0242 |
| 0.1153        | 25.0  | 2150 | 0.1722          | 0.0803 | 0.0230 |
| 0.1077        | 26.0  | 2236 | 0.1686          | 0.0766 | 0.0229 |
| 0.1239        | 27.0  | 2322 | 0.1763          | 0.0728 | 0.0221 |
| 0.1233        | 28.0  | 2408 | 0.1718          | 0.0766 | 0.0221 |
| 0.1233        | 29.0  | 2494 | 0.1822          | 0.0694 | 0.0211 |
| 0.101         | 30.0  | 2580 | 0.2026          | 0.0770 | 0.0234 |
| 0.1067        | 31.0  | 2666 | 0.1953          | 0.0759 | 0.0227 |
| 0.0966        | 32.0  | 2752 | 0.1917          | 0.0775 | 0.0230 |
| 0.1094        | 33.0  | 2838 | 0.1792          | 0.0819 | 0.0239 |
| 0.0922        | 34.0  | 2924 | 0.1951          | 0.0784 | 0.0229 |


### Framework versions

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