jayavibhav/DistillBERT-Prompt-Injection-sm

1---2license: apache-2.03base_model: distilbert-base-uncased4tags:5- generated_from_trainer6metrics:7- accuracy8model-index:9- name: DistillBERT-Prompt-Injection-sm10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# DistillBERT-Prompt-Injection-sm17 18This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.19It achieves the following results on the evaluation set:20- Loss: 0.029821- Accuracy: 0.993722 23## Model description24 25More information needed26 27## Intended uses & limitations28 29More information needed30 31## Training and evaluation data32 33More information needed34 35## Training procedure36 37### Training hyperparameters38 39The following hyperparameters were used during training:40- learning_rate: 2e-0541- train_batch_size: 1642- eval_batch_size: 1643- seed: 4244- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0845- lr_scheduler_type: linear46- num_epochs: 247 48### Training results49 50| Training Loss | Epoch | Step | Validation Loss | Accuracy |51|:-------------:|:-----:|:----:|:---------------:|:--------:|52| 0.0359        | 1.0   | 4688 | 0.0362          | 0.9917   |53| 0.0156        | 2.0   | 9376 | 0.0298          | 0.9937   |54 55 56### Framework versions57 58- Transformers 4.42.459- Pytorch 2.3.1+cu12160- Datasets 2.20.061- Tokenizers 0.19.162