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---
library_name: peft
license: mit
base_model: microsoft/Phi-4-mini-instruct
tags:
- generated_from_trainer
model-index:
- name: mitre_attack_model
  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. -->

# mitre_attack_model

This model is a fine-tuned version of [microsoft/Phi-4-mini-instruct](https://huggingface.co/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