---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-3B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama-3.2-3B-Instruct_sft_sg_values
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-3.2-3B-Instruct_sft_sg_values

This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the sft_sg_values dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2716

## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- 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: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3937        | 0.3738 | 250  | 0.3563          |
| 0.2652        | 0.7477 | 500  | 0.2791          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.21.1