Towards Explainable Classification of Non-Functional Requirements Using Fine-Tune-Chain-of-Thought Reasoning - Repo 2
<p>Supplementary material for <em>Towards Explainable Classification of Non-Functional Requirements Using Fine-Tune-Chain-of-Thought Reasoning </em></p> <div> <div> </div> <div>This version contains the llama2-7B model generated output for NFR identification on the PURE dataset. As discussed, the llama2-7B model mostly generated extraneous text. </div> <div> </div> <div>Llama2-7B generated output can be found in the column > <em>Model_output</em></div> <div>Input to Llama2-7B column > <em>llama_input_pure_test</em></div> <div> </div> <div><strong>Here is the link to repo 1 for accessing the fine-tuned models, code, and datasets > <a href="../records/10574330">https://zenodo.org/records/10574330</a></strong></div> </div>
ShareScore
16/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 8
- Reuse readiness
- 0
- Engagement
- 0