---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: LLMGUARD-roberta
  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-roberta

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6566
- Accuracy: 0.7760

## 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: 16
- 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.6725        | 1.0   | 1332  | 0.8128          | 0.7566   |
| 0.7216        | 2.0   | 2664  | 0.6906          | 0.7707   |
| 0.6441        | 3.0   | 3996  | 0.6679          | 0.7743   |
| 0.5968        | 4.0   | 5328  | 0.6599          | 0.7790   |
| 0.562         | 5.0   | 6660  | 0.6604          | 0.7777   |
| 0.5516        | 6.0   | 7992  | 0.6527          | 0.7763   |
| 0.5497        | 7.0   | 9324  | 0.6550          | 0.7767   |
| 0.513         | 8.0   | 10656 | 0.6566          | 0.7760   |


### Framework versions

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