---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: profesor_MViT_O_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_O_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: 0.2973
- Accuracy: 0.9237
- F1: 0.9237
- Precision: 0.9252
- Recall: 0.9237
- Roc Auc: 0.9762

## 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: 225
- training_steps: 2250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Roc Auc |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
| 0.4841        | 2.0324  | 225  | 0.3886          | 0.8947   | 0.8947 | 0.8947    | 0.8947 | 0.9512  |
| 0.2697        | 5.0311  | 450  | 0.2617          | 0.9158   | 0.9157 | 0.9175    | 0.9158 | 0.9655  |
| 0.1796        | 8.0298  | 675  | 0.2392          | 0.9184   | 0.9184 | 0.9190    | 0.9184 | 0.9725  |
| 0.1444        | 11.0284 | 900  | 0.2590          | 0.9184   | 0.9184 | 0.9187    | 0.9184 | 0.9755  |
| 0.1296        | 14.0271 | 1125 | 0.2587          | 0.9211   | 0.9210 | 0.9218    | 0.9211 | 0.9738  |
| 0.0952        | 17.0258 | 1350 | 0.2924          | 0.9211   | 0.9208 | 0.9258    | 0.9211 | 0.9719  |
| 0.1148        | 20.0244 | 1575 | 0.2497          | 0.9263   | 0.9263 | 0.9264    | 0.9263 | 0.9777  |
| 0.0969        | 23.0231 | 1800 | 0.2806          | 0.9289   | 0.9289 | 0.9304    | 0.9289 | 0.9775  |
| 0.0696        | 26.0218 | 2025 | 0.3203          | 0.9263   | 0.9263 | 0.9267    | 0.9263 | 0.9771  |
| 0.0915        | 29.0204 | 2250 | 0.3062          | 0.9263   | 0.9263 | 0.9263    | 0.9263 | 0.9740  |


### Framework versions

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