---
license: mit
base_model: microsoft/mdeberta-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/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1377
- Accuracy: 0.9376

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2424        | 1.0   | 293  | 0.1377          | 0.9376   |
| 0.1436        | 2.0   | 586  | 0.1565          | 0.9487   |
| 0.108         | 3.0   | 879  | 0.2244          | 0.9462   |
| 0.0806        | 4.0   | 1172 | 0.2356          | 0.9462   |
| 0.0548        | 5.0   | 1465 | 0.2658          | 0.9470   |
| 0.0473        | 6.0   | 1758 | 0.2437          | 0.9521   |
| 0.0339        | 7.0   | 2051 | 0.2838          | 0.9470   |
| 0.0199        | 8.0   | 2344 | 0.2974          | 0.9530   |
| 0.0193        | 9.0   | 2637 | 0.3392          | 0.9487   |
| 0.0176        | 10.0  | 2930 | 0.3296          | 0.9513   |


### Framework versions

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