---
library_name: transformers
license: other
base_model: meta-llama/Llama-3.2-3B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: Llama3.2-3B_Paper_Impact_SFT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama3.2-3B_Paper_Impact_SFT

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 paper_impact_sft_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1446

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use 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: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0607        | 0.7228 | 500  | 0.0733          |
| 0.029         | 1.4452 | 1000 | 0.0819          |
| 0.0058        | 2.1677 | 1500 | 0.1524          |
| 0.005         | 2.8905 | 2000 | 0.1443          |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.22.1