---
base_model: bert-base-uncased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: Balanced-KFold-ft-bert-base-uncased-for-binary-search
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Balanced-KFold-ft-bert-base-uncased-for-binary-search

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the network_vulnerability_dataset.csv dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5028
- Accuracy: 0.7256

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4316        | 1.0   | 87   | 0.5028          | 0.7256   |
| 0.5173        | 2.0   | 174  | 0.5019          | 0.7256   |
| 0.4516        | 3.0   | 261  | 0.5064          | 0.7256   |
| 0.4646        | 4.0   | 348  | 0.5050          | 0.7256   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1