---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Prompt-Guard-finetuned-ctf-86M
  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. -->

# Prompt-Guard-finetuned-ctf-86M

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0226
- Accuracy: 0.9964

## 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0291        | 1.0   | 2346  | 0.0315          | 0.9953   |
| 0.0222        | 2.0   | 4692  | 0.0318          | 0.9953   |
| 0.0081        | 3.0   | 7038  | 0.0226          | 0.9964   |
| 0.0032        | 4.0   | 9384  | 0.0329          | 0.9966   |
| 0.0031        | 5.0   | 11730 | 0.0352          | 0.9957   |
| 0.0039        | 6.0   | 14076 | 0.0242          | 0.9974   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.5.0+cu124
- Datasets 2.18.0
- Tokenizers 0.19.1