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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gelectra-base-injection-pt_v1
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. -->
# gelectra-base-injection-pt_v1
DEPRECATED - PLEASE USE NEWER GELECTRA OR DEBERTA VERSION
This model is a fine-tuned version of [deepset/gelectra-base](https://huggingface.co/deepset/gelectra-base) on a closed prompt injection dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0163
- Accuracy: 1.0
## Model description
The model classifies prompts as injections or legitimate questions.
## 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: 5e-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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 45 | 0.2042 | 0.9211 |
| No log | 2.0 | 90 | 0.0247 | 1.0 |
| No log | 3.0 | 135 | 0.0163 | 1.0 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3
|