metadata
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: []
Prompt-Guard-finetuned-ctf-86M
This model is a fine-tuned version of 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