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