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---
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
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