metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: deberta-v3-base-prompt-injection-v1
results: []
deberta-v3-base-prompt-injection-v1
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0010
- Accuracy: 0.9999
- Recall: 0.9997
- Precision: 0.9998
- F1: 0.9998
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 0.0038 | 1.0 | 36130 | 0.0026 | 0.9998 | 0.9994 | 0.9992 | 0.9993 |
| 0.0001 | 2.0 | 72260 | 0.0021 | 0.9998 | 0.9997 | 0.9989 | 0.9993 |
| 0.0 | 3.0 | 108390 | 0.0015 | 0.9999 | 0.9997 | 0.9995 | 0.9996 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0