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---
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
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