---
base_model: meta-llama/Llama-3.2-1B-Instruct
library_name: peft
license: other
tags:
- lora
- generated_from_trainer
model-index:
- name: sft_241015_1600_1
  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. -->

# sft_241015_1600_1

This model is a fine-tuned version of [/media/enssel/DataDisk/Models/Llama-3.2-3B-Instruct](https://huggingface.co//media/enssel/DataDisk/Models/Llama-3.2-3B-Instruct) on the app_logs_modified_1 and the NIST_SP_800_53 datasets.
It achieves the following results on the evaluation set:
- Loss: 1.8549

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

Application_logs and NIST_SP_800_53 datasets

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.9548        | 8.6957 | 50   | 1.8549          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1