---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: profesor_MViT_N_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_N_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: 0.2366
- Accuracy: 0.92
- F1: 0.9200
- Precision: 0.9205
- Recall: 0.92
- Roc Auc: 0.9722

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
| 0.5576        | 2.0333  | 240  | 0.4177          | 0.89     | 0.8900 | 0.8902    | 0.89   | 0.9554  |
| 0.2715        | 5.0333  | 480  | 0.2499          | 0.9225   | 0.9225 | 0.9234    | 0.9225 | 0.9768  |
| 0.1905        | 8.0333  | 720  | 0.2218          | 0.925    | 0.9250 | 0.9261    | 0.925  | 0.9799  |
| 0.1934        | 11.0333 | 960  | 0.2321          | 0.9125   | 0.9125 | 0.9125    | 0.9125 | 0.9791  |
| 0.1371        | 14.0333 | 1200 | 0.2527          | 0.9225   | 0.9224 | 0.9249    | 0.9225 | 0.9817  |


### Framework versions

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