---
license: apache-2.0
base_model: jackaduma/SecBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: dnrti_secbert
  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. -->

# dnrti_secbert

This model is a fine-tuned version of [jackaduma/SecBERT](https://huggingface.co/jackaduma/SecBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2274
- Precision: 0.7405
- Recall: 0.7780
- F1: 0.7588
- Accuracy: 0.9389

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6137        | 0.76  | 500  | 0.3731          | 0.5348    | 0.5951 | 0.5633 | 0.8842   |
| 0.2993        | 1.52  | 1000 | 0.2853          | 0.6684    | 0.6665 | 0.6674 | 0.9131   |
| 0.2157        | 2.28  | 1500 | 0.2624          | 0.6685    | 0.7282 | 0.6971 | 0.9212   |
| 0.152         | 3.04  | 2000 | 0.2414          | 0.6923    | 0.7619 | 0.7254 | 0.9308   |
| 0.1047        | 3.81  | 2500 | 0.2274          | 0.7405    | 0.7780 | 0.7588 | 0.9389   |
| 0.0725        | 4.57  | 3000 | 0.2563          | 0.7262    | 0.7964 | 0.7597 | 0.9370   |
| 0.0589        | 5.33  | 3500 | 0.2615          | 0.7489    | 0.8024 | 0.7747 | 0.9411   |
| 0.0442        | 6.09  | 4000 | 0.2638          | 0.7543    | 0.8061 | 0.7793 | 0.9434   |
| 0.0344        | 6.85  | 4500 | 0.2671          | 0.7635    | 0.8088 | 0.7855 | 0.9448   |
| 0.0282        | 7.61  | 5000 | 0.2861          | 0.7584    | 0.8111 | 0.7839 | 0.9439   |
| 0.0226        | 8.37  | 5500 | 0.2849          | 0.7693    | 0.8093 | 0.7888 | 0.9456   |
| 0.0207        | 9.13  | 6000 | 0.2932          | 0.7643    | 0.8185 | 0.7905 | 0.9456   |
| 0.0181        | 9.89  | 6500 | 0.2952          | 0.7665    | 0.8167 | 0.7908 | 0.9459   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1