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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
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