mitre_attack_model

This model is a fine-tuned version of microsoft/Phi-4-mini-instruct on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.6524

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• 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: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
2.9068	1.5201	50	2.7980
2.2862	3.0306	100	2.1574
1.8811	4.5507	150	1.8244
1.7806	6.0612	200	1.7332
1.7361	7.5813	250	1.6944
1.6709	9.0918	300	1.6713
1.6989	10.6119	350	1.6588
1.6858	12.1224	400	1.6524
1.6844	13.6424	450	1.6502

Framework versions

• PEFT 0.15.2
• Transformers 4.53.0
• Pytorch 2.6.0+cu124
• Datasets 2.14.4
• Tokenizers 0.21.2