---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: LLMGUARD-roberta-11
  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-11

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: 0.5908
- Accuracy: 0.8020

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.203         | 1.0   | 1585  | 0.8223          | 0.7612   |
| 0.696         | 2.0   | 3170  | 0.6380          | 0.7964   |
| 0.6014        | 3.0   | 4755  | 0.6126          | 0.7997   |
| 0.5652        | 4.0   | 6340  | 0.5943          | 0.8026   |
| 0.5346        | 5.0   | 7925  | 0.5890          | 0.8018   |
| 0.5118        | 6.0   | 9510  | 0.5860          | 0.8035   |
| 0.4702        | 7.0   | 11095 | 0.5901          | 0.8034   |
| 0.489         | 8.0   | 12680 | 0.5908          | 0.8020   |


### Framework versions

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