stage1_binary_checkpoints

This model is a fine-tuned version of meta-llama/Llama-Prompt-Guard-2-22M on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1929
• F1: 0.9596
• Accuracy: 0.964

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-05
• train_batch_size: 2
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.3784	1.0	1063	0.1929	0.9596	0.964

Framework versions

• Transformers 5.16.1
• Pytorch 2.11.0+cpu
• Datasets 4.0.0
• Tokenizers 0.23.1