---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: estudiante_Swin3D_RLVS
  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. -->

# estudiante_Swin3D_RLVS

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0766
- Accuracy: 0.9816
- F1: 0.9816
- Precision: 0.9817
- Recall: 0.9816
- Roc Auc: 0.9988

## 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: 1e-05
- train_batch_size: 15
- eval_batch_size: 15
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 318
- training_steps: 3180
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Roc Auc |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
| 0.2317        | 1.0160  | 159  | 0.1561          | 0.9412   | 0.9410 | 0.9453    | 0.9412 | 0.9878  |
| 0.1354        | 2.0321  | 318  | 0.0908          | 0.9652   | 0.9652 | 0.9654    | 0.9652 | 0.9939  |
| 0.0698        | 4.0142  | 477  | 0.1050          | 0.9679   | 0.9679 | 0.9688    | 0.9679 | 0.9952  |
| 0.0767        | 5.0302  | 636  | 0.0930          | 0.9759   | 0.9759 | 0.9761    | 0.9759 | 0.9972  |
| 0.0576        | 7.0123  | 795  | 0.0916          | 0.9786   | 0.9786 | 0.9787    | 0.9786 | 0.9975  |
| 0.0514        | 8.0283  | 954  | 0.0840          | 0.9813   | 0.9813 | 0.9814    | 0.9813 | 0.9985  |
| 0.0481        | 10.0104 | 1113 | 0.1026          | 0.9733   | 0.9733 | 0.9733    | 0.9733 | 0.9980  |
| 0.0257        | 11.0264 | 1272 | 0.1148          | 0.9813   | 0.9813 | 0.9814    | 0.9813 | 0.9966  |
| 0.03          | 13.0085 | 1431 | 0.1170          | 0.9759   | 0.9759 | 0.9761    | 0.9759 | 0.9981  |
| 0.0302        | 14.0245 | 1590 | 0.1537          | 0.9733   | 0.9733 | 0.9735    | 0.9733 | 0.9978  |
| 0.0414        | 16.0066 | 1749 | 0.1367          | 0.9786   | 0.9786 | 0.9787    | 0.9786 | 0.9981  |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.0.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3