---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training_outputs
  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. -->

# training_outputs

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0394
- Accuracy: 0.993
- Precision: 0.9913
- Recall: 0.9884
- F1: 0.9899
- Roc Auc: 0.9988

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.045         | 0.1105 | 1000 | 0.0609          | 0.987    | 0.9798    | 0.9827 | 0.9812 | 0.9990  |
| 0.0539        | 0.2210 | 2000 | 0.0471          | 0.988    | 0.9883    | 0.9769 | 0.9826 | 0.9985  |
| 0.0467        | 0.3316 | 3000 | 0.0546          | 0.989    | 0.9855    | 0.9827 | 0.9841 | 0.9989  |
| 0.0439        | 0.4421 | 4000 | 0.0416          | 0.99     | 0.9884    | 0.9827 | 0.9855 | 0.9990  |
| 0.0419        | 0.5526 | 5000 | 0.0470          | 0.99     | 0.9855    | 0.9855 | 0.9855 | 0.9991  |
| 0.0395        | 0.6631 | 6000 | 0.0396          | 0.992    | 0.9884    | 0.9884 | 0.9884 | 0.9970  |
| 0.0329        | 0.7737 | 7000 | 0.0427          | 0.993    | 0.9885    | 0.9913 | 0.9899 | 0.9986  |
| 0.0373        | 0.8842 | 8000 | 0.0408          | 0.992    | 0.9884    | 0.9884 | 0.9884 | 0.9988  |
| 0.031         | 0.9947 | 9000 | 0.0394          | 0.993    | 0.9913    | 0.9884 | 0.9899 | 0.9988  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1