|
|
--- |
|
|
license: mit |
|
|
base_model: microsoft/deberta-v3-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
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: 0.0155 |
|
|
- Accuracy: 0.9972 |
|
|
- Precision: 0.9972 |
|
|
- Recall: 0.9972 |
|
|
- F1: 0.9972 |
|
|
|
|
|
## 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 | Precision | Recall | F1 | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
|
| 0.0364 | 1.0 | 2344 | 0.0224 | 0.9964 | 0.9964 | 0.9964 | 0.9964 | |
|
|
| 0.038 | 2.0 | 4688 | 0.0405 | 0.9893 | 0.9907 | 0.9893 | 0.9897 | |
|
|
| 0.0126 | 3.0 | 7032 | 0.0211 | 0.9962 | 0.9962 | 0.9962 | 0.9962 | |
|
|
| 0.0077 | 4.0 | 9376 | 0.0206 | 0.9966 | 0.9966 | 0.9966 | 0.9966 | |
|
|
| 0.0038 | 5.0 | 11720 | 0.0155 | 0.9972 | 0.9972 | 0.9972 | 0.9972 | |
|
|
| 0.0015 | 6.0 | 14064 | 0.0201 | 0.9972 | 0.9972 | 0.9972 | 0.9972 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.40.2 |
|
|
- Pytorch 2.5.0+cu124 |
|
|
- Datasets 2.18.0 |
|
|
- Tokenizers 0.19.1 |
|
|
|
