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# Metricas_teste_wan

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1473
- Accuracy: 0.9818

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 248   | 0.3574          | 0.9114   |
| No log        | 2.0   | 496   | 0.1911          | 0.9386   |
| 0.7732        | 3.0   | 744   | 0.1919          | 0.9386   |
| 0.7732        | 4.0   | 992   | 0.1044          | 0.9727   |
| 0.0987        | 5.0   | 1240  | 0.0928          | 0.9682   |
| 0.0987        | 6.0   | 1488  | 0.0545          | 0.9841   |
| 0.0406        | 7.0   | 1736  | 0.1183          | 0.9727   |
| 0.0406        | 8.0   | 1984  | 0.1114          | 0.9773   |
| 0.0204        | 9.0   | 2232  | 0.0838          | 0.9773   |
| 0.0204        | 10.0  | 2480  | 0.0726          | 0.9818   |
| 0.0084        | 11.0  | 2728  | 0.1100          | 0.975    |
| 0.0084        | 12.0  | 2976  | 0.1133          | 0.9773   |
| 0.0032        | 13.0  | 3224  | 0.1283          | 0.9773   |
| 0.0032        | 14.0  | 3472  | 0.0935          | 0.9795   |
| 0.0084        | 15.0  | 3720  | 0.1318          | 0.9705   |
| 0.0084        | 16.0  | 3968  | 0.1446          | 0.9773   |
| 0.0031        | 17.0  | 4216  | 0.1123          | 0.9773   |
| 0.0031        | 18.0  | 4464  | 0.0971          | 0.975    |
| 0.0049        | 19.0  | 4712  | 0.1369          | 0.9773   |
| 0.0049        | 20.0  | 4960  | 0.1855          | 0.9773   |
| 0.0018        | 21.0  | 5208  | 0.2224          | 0.9659   |
| 0.0018        | 22.0  | 5456  | 0.1444          | 0.9795   |
| 0.0045        | 23.0  | 5704  | 0.1544          | 0.9795   |
| 0.0045        | 24.0  | 5952  | 0.1495          | 0.9705   |
| 0.0037        | 25.0  | 6200  | 0.1741          | 0.975    |
| 0.0037        | 26.0  | 6448  | 0.1658          | 0.9705   |
| 0.0001        | 27.0  | 6696  | 0.2132          | 0.9727   |
| 0.0001        | 28.0  | 6944  | 0.2222          | 0.9682   |
| 0.0079        | 29.0  | 7192  | 0.1348          | 0.9795   |
| 0.0079        | 30.0  | 7440  | 0.1656          | 0.9773   |
| 0.0016        | 31.0  | 7688  | 0.1584          | 0.975    |
| 0.0016        | 32.0  | 7936  | 0.1674          | 0.9795   |
| 0.0005        | 33.0  | 8184  | 0.1837          | 0.9795   |
| 0.0005        | 34.0  | 8432  | 0.1595          | 0.9773   |
| 0.0016        | 35.0  | 8680  | 0.1949          | 0.9795   |
| 0.0016        | 36.0  | 8928  | 0.0991          | 0.9818   |
| 0.0004        | 37.0  | 9176  | 0.1864          | 0.9795   |
| 0.0004        | 38.0  | 9424  | 0.1444          | 0.9795   |
| 0.0024        | 39.0  | 9672  | 0.1486          | 0.9773   |
| 0.0024        | 40.0  | 9920  | 0.1457          | 0.9773   |
| 0.0004        | 41.0  | 10168 | 0.1486          | 0.9773   |
| 0.0004        | 42.0  | 10416 | 0.1518          | 0.9773   |
| 0.0           | 43.0  | 10664 | 0.1517          | 0.9773   |
| 0.0           | 44.0  | 10912 | 0.1480          | 0.9773   |
| 0.0           | 45.0  | 11160 | 0.1458          | 0.9818   |
| 0.0           | 46.0  | 11408 | 0.1462          | 0.9818   |
| 0.0           | 47.0  | 11656 | 0.1466          | 0.9818   |
| 0.0           | 48.0  | 11904 | 0.1470          | 0.9818   |
| 0.0           | 49.0  | 12152 | 0.1472          | 0.9818   |
| 0.0           | 50.0  | 12400 | 0.1473          | 0.9818   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "Metricas_teste_wan", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us