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# bert_ENEM

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0267
- Accuracy: 0.3611

## 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: 5e-05
- train_batch_size: 3
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 107  | 1.6131          | 0.25     |
| No log        | 2.0   | 214  | 1.5635          | 0.3333   |
| No log        | 3.0   | 321  | 1.4007          | 0.4444   |
| No log        | 4.0   | 428  | 1.9448          | 0.4167   |
| 1.137         | 5.0   | 535  | 2.1251          | 0.4167   |
| 1.137         | 6.0   | 642  | 2.4106          | 0.3889   |
| 1.137         | 7.0   | 749  | 2.5102          | 0.3333   |
| 1.137         | 8.0   | 856  | 2.6479          | 0.4167   |
| 1.137         | 9.0   | 963  | 2.9045          | 0.3889   |
| 0.0629        | 10.0  | 1070 | 3.0267          | 0.3611   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "neuralmind/bert-base-portuguese-cased", "model-index": [{"name": "bert_ENEM", "results": []}]}
transformers safetensors bert multiple-choice generated_from_trainer base_model:neuralmind/bert-base-portuguese-cased license:mit endpoints_compatible region:us