---
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: 1.3081
- Accuracy: 0.7230

## 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: 1e-05
- 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_steps: 500
- num_epochs: 32
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5456        | 1.0   | 876   | 0.6853          | 0.7600   |
| 0.6286        | 2.0   | 1752  | 0.6386          | 0.7755   |
| 0.5239        | 3.0   | 2628  | 0.6216          | 0.7690   |
| 0.4708        | 4.0   | 3504  | 0.6294          | 0.7684   |
| 0.4224        | 5.0   | 4380  | 0.6622          | 0.7690   |
| 0.3963        | 6.0   | 5256  | 0.6938          | 0.7558   |
| 0.3677        | 7.0   | 6132  | 0.7313          | 0.7575   |
| 0.3486        | 8.0   | 7008  | 0.7668          | 0.7508   |
| 0.3192        | 9.0   | 7884  | 0.7856          | 0.7488   |
| 0.3119        | 10.0  | 8760  | 0.8193          | 0.7413   |
| 0.297         | 11.0  | 9636  | 0.8250          | 0.7385   |
| 0.2826        | 12.0  | 10512 | 0.8906          | 0.7264   |
| 0.2664        | 13.0  | 11388 | 0.8942          | 0.7301   |
| 0.2614        | 14.0  | 12264 | 0.9402          | 0.7281   |
| 0.2585        | 15.0  | 13140 | 0.9722          | 0.7361   |
| 0.2603        | 16.0  | 14016 | 1.0199          | 0.7285   |
| 0.2366        | 17.0  | 14892 | 1.0044          | 0.7290   |
| 0.2406        | 18.0  | 15768 | 1.0022          | 0.7237   |
| 0.2341        | 19.0  | 16644 | 1.0498          | 0.7233   |
| 0.2392        | 20.0  | 17520 | 1.0741          | 0.7258   |
| 0.2135        | 21.0  | 18396 | 1.1113          | 0.7233   |
| 0.2166        | 22.0  | 19272 | 1.1229          | 0.7288   |
| 0.216         | 23.0  | 20148 | 1.1429          | 0.7204   |
| 0.2164        | 24.0  | 21024 | 1.1872          | 0.7261   |
| 0.2079        | 25.0  | 21900 | 1.2140          | 0.7161   |
| 0.2027        | 26.0  | 22776 | 1.2285          | 0.7240   |
| 0.201         | 27.0  | 23652 | 1.2247          | 0.7250   |
| 0.2052        | 28.0  | 24528 | 1.2356          | 0.7207   |
| 0.1959        | 29.0  | 25404 | 1.2895          | 0.7217   |
| 0.1975        | 30.0  | 26280 | 1.2861          | 0.7245   |
| 0.1937        | 31.0  | 27156 | 1.3034          | 0.7211   |
| 0.194         | 32.0  | 28032 | 1.3081          | 0.7230   |


### Framework versions

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