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-08
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-xlsr-1b-mecita-portuguese-all-clean-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: 0.1311
- Wer: 0.0811
- Cer: 0.0222

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 24.4001       | 1.0   | 67   | 2.9064          | 1.0    | 1.0    |
| 5.3927        | 2.0   | 134  | 0.7600          | 0.6051 | 0.1435 |
| 1.2383        | 3.0   | 201  | 0.1986          | 0.1251 | 0.0340 |
| 1.2383        | 4.0   | 268  | 0.1653          | 0.1000 | 0.0279 |
| 0.347         | 5.0   | 335  | 0.1546          | 0.0890 | 0.0258 |
| 0.2814        | 6.0   | 402  | 0.1446          | 0.0947 | 0.0260 |
| 0.2814        | 7.0   | 469  | 0.1518          | 0.0904 | 0.0257 |
| 0.269         | 8.0   | 536  | 0.1387          | 0.0967 | 0.0265 |
| 0.2346        | 9.0   | 603  | 0.1439          | 0.0914 | 0.0251 |
| 0.2346        | 10.0  | 670  | 0.1438          | 0.0907 | 0.0262 |
| 0.1908        | 11.0  | 737  | 0.1335          | 0.0834 | 0.0234 |
| 0.1799        | 12.0  | 804  | 0.1338          | 0.0844 | 0.0237 |
| 0.1799        | 13.0  | 871  | 0.1452          | 0.0844 | 0.0235 |
| 0.1866        | 14.0  | 938  | 0.1484          | 0.0884 | 0.0252 |
| 0.1667        | 15.0  | 1005 | 0.1518          | 0.0837 | 0.0241 |
| 0.1667        | 16.0  | 1072 | 0.1406          | 0.0857 | 0.0240 |
| 0.147         | 17.0  | 1139 | 0.1490          | 0.0857 | 0.0248 |
| 0.1476        | 18.0  | 1206 | 0.1579          | 0.0851 | 0.0250 |
| 0.1476        | 19.0  | 1273 | 0.1439          | 0.0801 | 0.0234 |
| 0.1571        | 20.0  | 1340 | 0.1484          | 0.0781 | 0.0239 |
| 0.1229        | 21.0  | 1407 | 0.1391          | 0.0755 | 0.0222 |
| 0.1229        | 22.0  | 1474 | 0.1525          | 0.0831 | 0.0244 |
| 0.1146        | 23.0  | 1541 | 0.1458          | 0.0814 | 0.0232 |
| 0.1164        | 24.0  | 1608 | 0.1453          | 0.0831 | 0.0243 |
| 0.1164        | 25.0  | 1675 | 0.1311          | 0.0811 | 0.0222 |
| 0.1145        | 26.0  | 1742 | 0.1397          | 0.0847 | 0.0247 |
| 0.0973        | 27.0  | 1809 | 0.1455          | 0.0844 | 0.0242 |
| 0.0973        | 28.0  | 1876 | 0.1395          | 0.0834 | 0.0227 |
| 0.1097        | 29.0  | 1943 | 0.1450          | 0.0821 | 0.0237 |
| 0.1072        | 30.0  | 2010 | 0.1456          | 0.0831 | 0.0237 |
| 0.1072        | 31.0  | 2077 | 0.1449          | 0.0801 | 0.0230 |
| 0.0927        | 32.0  | 2144 | 0.1637          | 0.0824 | 0.0241 |
| 0.0873        | 33.0  | 2211 | 0.1528          | 0.0828 | 0.0236 |
| 0.0873        | 34.0  | 2278 | 0.1518          | 0.0771 | 0.0230 |
| 0.0772        | 35.0  | 2345 | 0.1633          | 0.0778 | 0.0237 |
| 0.1025        | 36.0  | 2412 | 0.1462          | 0.0798 | 0.0227 |
| 0.1025        | 37.0  | 2479 | 0.1443          | 0.0781 | 0.0230 |
| 0.0919        | 38.0  | 2546 | 0.1486          | 0.0794 | 0.0230 |
| 0.0747        | 39.0  | 2613 | 0.1501          | 0.0791 | 0.0235 |
| 0.0747        | 40.0  | 2680 | 0.1596          | 0.0775 | 0.0224 |
| 0.0739        | 41.0  | 2747 | 0.1662          | 0.0811 | 0.0240 |
| 0.068         | 42.0  | 2814 | 0.1605          | 0.0808 | 0.0236 |
| 0.068         | 43.0  | 2881 | 0.1597          | 0.0788 | 0.0229 |
| 0.078         | 44.0  | 2948 | 0.1556          | 0.0765 | 0.0223 |
| 0.0656        | 45.0  | 3015 | 0.1566          | 0.0741 | 0.0218 |


### Framework versions

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