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---
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
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