---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: profesor_MViT_B_RWF2000
  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. -->

# profesor_MViT_B_RWF2000

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: 0.2639
- Accuracy: 0.9225
- F1: 0.9225
- Precision: 0.9225
- Recall: 0.9225
- Roc Auc: 0.9782

## 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: 20
- eval_batch_size: 20
- 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: 240
- training_steps: 2400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Roc Auc |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
| 0.5302        | 2.0333  | 240  | 0.4018          | 0.895    | 0.895  | 0.895     | 0.895  | 0.9609  |
| 0.2816        | 5.0333  | 480  | 0.2559          | 0.9125   | 0.9125 | 0.9126    | 0.9125 | 0.9782  |
| 0.1884        | 8.0333  | 720  | 0.2456          | 0.91     | 0.9099 | 0.9115    | 0.91   | 0.9799  |
| 0.1991        | 11.0333 | 960  | 0.2289          | 0.9225   | 0.9225 | 0.9225    | 0.9225 | 0.9815  |
| 0.1298        | 14.0333 | 1200 | 0.2186          | 0.9275   | 0.9275 | 0.9275    | 0.9275 | 0.9834  |
| 0.1518        | 17.0333 | 1440 | 0.2484          | 0.9275   | 0.9275 | 0.9276    | 0.9275 | 0.9798  |
| 0.107         | 20.0333 | 1680 | 0.2442          | 0.93     | 0.9300 | 0.9300    | 0.93   | 0.9834  |
| 0.1021        | 23.0333 | 1920 | 0.2653          | 0.925    | 0.9250 | 0.9252    | 0.925  | 0.9813  |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.0.1+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1