--- tags: - LLM - Qwen - Indonesia - PPN - PPnBM - Finance - Tax - Bahasa Indonesia - Fine-tuning - QLoRA - QA language: id model_name: Qwen2.5-7B-Instruct-PPN-PPnBM-Merged datasets: - dataset_ppn_ppnbm_v2_clean.jsonl metrics: - name: ROUGE-1 type: rouge value: 0.3059 - name: ROUGE-2 type: rouge value: 0.1078 - name: ROUGE-L type: rouge value: 0.2638 - name: ROUGE-Lsum type: rouge value: 0.2645 summary: | Model bahasa Qwen2.5-7B-Instruct yang di-fine-tuned menggunakan QLoRA dengan dataset pertanyaan-jawaban seputar Pajak Pertambahan Nilai (PPN) dan Pajak Penjualan atas Barang Mewah (PPnBM) di Indonesia, berdasarkan UU No. 8/1983 s.t.d.t.d. UU No. 7/2021 (UU HPP). Model ini dirancang untuk menjawab pertanyaan perpajakan dengan akurat dan memberikan rujukan pasal yang relevan. Ini adalah versi yang telah di-merge (menggabungkan LoRA adapters ke base model). base_model: Qwen/Qwen2.5-7B-Instruct finetuned_from: Qwen/Qwen2.5-7B-Instruct pipeline_tag: text-generation inference_with_peft: false --- # Model Card for qwen25-ppn-ppnbm-merged-model ## Model Details ### Model Description - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** id - **Finetuned from model [optional]:** Qwen/Qwen2.5-7B-Instruct ### Model Sources [optional] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses ### Direct Use [More Information Needed] ### Downstream Use [optional] [More Information Needed] ### Out-of-Scope Use [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ### Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] [More Information Needed] ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]