README.md

---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- generated_from_trainer
datasets:
- scitldr
model-index:
- name: Llama-3.2-1B-Summarization-LoRa
  results: []
pipeline_tag: summarization
---

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# Llama-3.2-1B-Summarization-LoRa

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on the scitldr dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5661

## Model description

Fine-tuned (LoRa) Version of meta-llama/Llama-3.2-1B for Summarization of scientific documents

## Intended uses & limitations

Summarization

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.45          | 0.2008 | 200  | 2.5272          |
| 2.4331        | 0.4016 | 400  | 2.5327          |
| 2.4369        | 0.6024 | 600  | 2.5285          |
| 2.4315        | 0.8032 | 800  | 2.5238          |
| 2.4303        | 1.0040 | 1000 | 2.5181          |
| 2.1077        | 1.2048 | 1200 | 2.5525          |
| 2.0951        | 1.4056 | 1400 | 2.5611          |
| 2.0738        | 1.6064 | 1600 | 2.5591          |
| 2.0539        | 1.8072 | 1800 | 2.5661          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3