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# clasificador-de-pesos

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0739
- Accuracy: 0.9843

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0999        | 0.96  | 13   | 0.7987          | 0.6440   |
| 0.6342        | 2.0   | 27   | 0.2414          | 0.9424   |
| 0.4882        | 2.96  | 40   | 0.1646          | 0.9634   |
| 0.463         | 4.0   | 54   | 0.2528          | 0.9424   |
| 0.4609        | 4.96  | 67   | 0.1130          | 0.9791   |
| 0.4251        | 6.0   | 81   | 0.1304          | 0.9634   |
| 0.3802        | 6.96  | 94   | 0.0739          | 0.9843   |
| 0.4147        | 7.7   | 104  | 0.0675          | 0.9843   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1

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