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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-01

This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1429
- Wer: 0.0862
- Cer: 0.0263

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 31.9255       | 1.0   | 86   | 3.2559          | 1.0    | 1.0    |
| 8.1132        | 2.0   | 172  | 3.0009          | 1.0    | 1.0    |
| 3.0533        | 3.0   | 258  | 2.9120          | 1.0    | 1.0    |
| 2.93          | 4.0   | 344  | 2.8877          | 1.0    | 1.0    |
| 2.8396        | 5.0   | 430  | 1.9900          | 1.0    | 0.7238 |
| 1.8884        | 6.0   | 516  | 0.6068          | 0.3305 | 0.0859 |
| 0.8835        | 7.0   | 602  | 0.3984          | 0.2086 | 0.0553 |
| 0.8835        | 8.0   | 688  | 0.3249          | 0.1780 | 0.0492 |
| 0.6254        | 9.0   | 774  | 0.2698          | 0.1662 | 0.0450 |
| 0.5176        | 10.0  | 860  | 0.2420          | 0.1408 | 0.0400 |
| 0.4379        | 11.0  | 946  | 0.2315          | 0.1322 | 0.0376 |
| 0.3823        | 12.0  | 1032 | 0.2185          | 0.1261 | 0.0356 |
| 0.3601        | 13.0  | 1118 | 0.2176          | 0.1148 | 0.0344 |
| 0.3457        | 14.0  | 1204 | 0.2050          | 0.1119 | 0.0330 |
| 0.3457        | 15.0  | 1290 | 0.1928          | 0.1048 | 0.0306 |
| 0.2942        | 16.0  | 1376 | 0.1864          | 0.0994 | 0.0305 |
| 0.3054        | 17.0  | 1462 | 0.1826          | 0.0987 | 0.0297 |
| 0.321         | 18.0  | 1548 | 0.1755          | 0.0974 | 0.0298 |
| 0.2667        | 19.0  | 1634 | 0.1743          | 0.0996 | 0.0297 |
| 0.2706        | 20.0  | 1720 | 0.1720          | 0.0965 | 0.0288 |
| 0.2355        | 21.0  | 1806 | 0.1646          | 0.0935 | 0.0283 |
| 0.2355        | 22.0  | 1892 | 0.1645          | 0.0935 | 0.0287 |
| 0.2355        | 23.0  | 1978 | 0.1583          | 0.0891 | 0.0271 |
| 0.2401        | 24.0  | 2064 | 0.1578          | 0.0923 | 0.0283 |
| 0.236         | 25.0  | 2150 | 0.1587          | 0.0894 | 0.0280 |
| 0.2314        | 26.0  | 2236 | 0.1547          | 0.0896 | 0.0274 |
| 0.2209        | 27.0  | 2322 | 0.1513          | 0.0891 | 0.0266 |
| 0.2269        | 28.0  | 2408 | 0.1550          | 0.0891 | 0.0270 |
| 0.2269        | 29.0  | 2494 | 0.1566          | 0.0898 | 0.0273 |
| 0.2123        | 30.0  | 2580 | 0.1572          | 0.0898 | 0.0273 |
| 0.1941        | 31.0  | 2666 | 0.1518          | 0.0867 | 0.0266 |
| 0.2108        | 32.0  | 2752 | 0.1492          | 0.0869 | 0.0266 |
| 0.187         | 33.0  | 2838 | 0.1479          | 0.0864 | 0.0268 |
| 0.1799        | 34.0  | 2924 | 0.1429          | 0.0862 | 0.0263 |
| 0.1804        | 35.0  | 3010 | 0.1472          | 0.0835 | 0.0257 |
| 0.1804        | 36.0  | 3096 | 0.1457          | 0.0857 | 0.0262 |
| 0.1756        | 37.0  | 3182 | 0.1456          | 0.0830 | 0.0254 |
| 0.1684        | 38.0  | 3268 | 0.1459          | 0.0857 | 0.0259 |
| 0.1692        | 39.0  | 3354 | 0.1461          | 0.0840 | 0.0263 |
| 0.1609        | 40.0  | 3440 | 0.1432          | 0.0837 | 0.0260 |
| 0.1877        | 41.0  | 3526 | 0.1475          | 0.0818 | 0.0253 |
| 0.1611        | 42.0  | 3612 | 0.1434          | 0.0830 | 0.0261 |
| 0.1611        | 43.0  | 3698 | 0.1438          | 0.0827 | 0.0247 |
| 0.1887        | 44.0  | 3784 | 0.1478          | 0.0832 | 0.0255 |
| 0.1712        | 45.0  | 3870 | 0.1493          | 0.0842 | 0.0257 |
| 0.1531        | 46.0  | 3956 | 0.1493          | 0.0803 | 0.0250 |
| 0.1605        | 47.0  | 4042 | 0.1479          | 0.0842 | 0.0257 |
| 0.1599        | 48.0  | 4128 | 0.1455          | 0.0818 | 0.0250 |
| 0.1623        | 49.0  | 4214 | 0.1470          | 0.0823 | 0.0252 |
| 0.1601        | 50.0  | 4300 | 0.1474          | 0.0793 | 0.0252 |
| 0.1601        | 51.0  | 4386 | 0.1491          | 0.0798 | 0.0250 |
| 0.1478        | 52.0  | 4472 | 0.1491          | 0.0796 | 0.0254 |
| 0.1497        | 53.0  | 4558 | 0.1481          | 0.0815 | 0.0249 |
| 0.1454        | 54.0  | 4644 | 0.1455          | 0.0796 | 0.0245 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-01", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us