---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: LLMGUARD
  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. -->

# LLMGUARD

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co./distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6730
- Accuracy: 0.7628

## 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-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 32
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.2334        | 1.0   | 876   | 1.8027          | 0.4071   |
| 1.6018        | 2.0   | 1752  | 1.1836          | 0.6644   |
| 0.9703        | 3.0   | 2628  | 0.8345          | 0.7433   |
| 0.7557        | 4.0   | 3504  | 0.7281          | 0.7591   |
| 0.7028        | 5.0   | 4380  | 0.6809          | 0.7717   |
| 0.6372        | 6.0   | 5256  | 0.6530          | 0.7768   |
| 0.6074        | 7.0   | 6132  | 0.6411          | 0.7787   |
| 0.5809        | 8.0   | 7008  | 0.6292          | 0.7785   |
| 0.5594        | 9.0   | 7884  | 0.6255          | 0.7832   |
| 0.5452        | 10.0  | 8760  | 0.6334          | 0.7797   |
| 0.5334        | 11.0  | 9636  | 0.6225          | 0.7761   |
| 0.5091        | 12.0  | 10512 | 0.6347          | 0.7734   |
| 0.493         | 13.0  | 11388 | 0.6217          | 0.7794   |
| 0.4883        | 14.0  | 12264 | 0.6259          | 0.7782   |
| 0.4746        | 15.0  | 13140 | 0.6265          | 0.7725   |
| 0.4698        | 16.0  | 14016 | 0.6351          | 0.7728   |
| 0.4531        | 17.0  | 14892 | 0.6401          | 0.7734   |
| 0.4579        | 18.0  | 15768 | 0.6435          | 0.7731   |
| 0.4412        | 19.0  | 16644 | 0.6391          | 0.7710   |
| 0.4377        | 20.0  | 17520 | 0.6432          | 0.7705   |
| 0.4362        | 21.0  | 18396 | 0.6500          | 0.7681   |
| 0.4269        | 22.0  | 19272 | 0.6541          | 0.7674   |
| 0.4227        | 23.0  | 20148 | 0.6555          | 0.7658   |
| 0.4196        | 24.0  | 21024 | 0.6569          | 0.7678   |
| 0.4216        | 25.0  | 21900 | 0.6608          | 0.7660   |
| 0.4107        | 26.0  | 22776 | 0.6651          | 0.7672   |
| 0.4118        | 27.0  | 23652 | 0.6629          | 0.7645   |
| 0.4054        | 28.0  | 24528 | 0.6685          | 0.7624   |
| 0.4112        | 29.0  | 25404 | 0.6705          | 0.7642   |
| 0.3999        | 30.0  | 26280 | 0.6724          | 0.7625   |
| 0.405         | 31.0  | 27156 | 0.6721          | 0.7628   |
| 0.394         | 32.0  | 28032 | 0.6730          | 0.7628   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0