gabe-zhang
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Llama-PaperSummarization-LoRA

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 ---
 library_name: transformers
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 ---
 library_name: transformers
+tags:
+- paper-summarization
+- lora
+- peft
+- llama
+license: mit
+datasets:
+- armanc/scientific_papers
+language:
+- en
+metrics:
+- rouge
+base_model:
+- meta-llama/Llama-3.2-1B-Instruct
+pipeline_tag: summarization
 ---
+# **Llama-PaperSummarization-LoRA**
+## **Model Details**
+This is a **LoRA fine-tuned adapter** built on [**meta-llama/Llama-3.2-1B-Instruct**](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct). It is designed for scientific paper summarization tasks and leverages **Low-Rank Adaptation (LoRA)** to enhance model performance efficiently while maintaining a low computational overhead.
+---
+## **Dataset**
+The model was fine-tuned on the [**armanc/scientific_papers**](https://huggingface.co/datasets/armanc/scientific_papers) dataset. Below are the details of the dataset splits:
+- **Training Set**: 20K samples
+- **Validation Set**: 6K samples
+---
+## **LoRA Configuration**
+- **Trainable Parameters**: 850K (~7% of base model parameters)
+- **Context Length**: 10K tokens
+- **Rank**: 8
+- **Target Modules**: Query and Value matrices
+- **Optimization Settings**:
+  - Gradient Accumulation: 4 steps
+  - Training Steps: 5K
+### **Training Setup**
+- **Hardware**: NVIDIA RTX A6000 GPU
+- **Evaluation Frequency**: Every 20 steps
+- **Training Duration**: 28 hours
+- **Training Scripts**: [gabe-zhang/paper2summary](https://github.com/gabe-zhang/paper2summary)
+---
+## **Evaluation**
+The model was evaluated on a **6K-sample test set** using **ROUGE scores** with the following settings:
+- **Decoding Strategy**: Beam search (beam size = 4)
+### **Performance Comparison**
+| Model                     | ROUGE-1 | ROUGE-2 | ROUGE-3 | ROUGE-L |
+|---------------------------|----------|----------|----------|----------|
+| **Llama-3.2-1B-Instruct** | 36.69    | 7.47     | 1.95     | 19.36    |
+| **Llama-PaperSummarization-LoRA** | **41.56** | **11.31** | **2.67** | **21.86** |
+---
+## **License**
+This repository contains a **LoRA fine-tuned adapter** derived from the Llama 3.2 model.
+- **Llama 3.2 Materials**: Governed by the [Llama 3.2 Community License](./LICENSE_Llama3.2).
+- **All other content**: Licensed under the [MIT License](./LICENSE).
+### **Attribution**
+- The model prominently incorporates Llama 3.2 as its base.
+- "Built with Llama" is displayed as required by the Llama 3.2 Community License.