In line with previous studies , the "StructureMatcher" class in pymatgen is used for comparison between generated crystal structures to the ground-truth structures, with thresholds set as follows: fractional length tolerance (ltol) = 0.3, site tolerance (stol) = 0.5, and angle tolerance (angle_tol) = 10. These parameters determine whether a generated structure matches the groundtruth structure. For each structure in the test set, we generate N = 20 samples with the same composition and space group number. When N = 1, only the first generated sample for each test entry is considered, representing a single attempt per structure, and the RMSE is calculated if a match is found. When N = 20, we assess whether any of the 20 generated samples match the ground-truth structure. The match rate is defined as the percentage of test structures for which at least one matching sample is found. For matched structures, the RMSE is calculated between the ground-truth and the best-matching candidate, and this value is averaged across all matched structures. Table . shows the evaluation results on the MP-20 dataset, detailing match rates and RMSE values for both N=1 and N =20. The performance of the fine-tuned model was evaluated on a held-out dataset to assess its ability to meet specific conditions. Figure (a) represents the satisfaction rates for the model's performance in generating crystal structures that meet the conditions of composition and space group number. This bar plot showcases how well the model satisfies each of these conditions in the held-out dataset. The model demonstrated a high success rate of 95% in generating structures that matched the ground-truth composition, showcasing its strong capability in producing structures with the correct elemental makeup. The accuracy for generating structures with the correct space group number and for satisfying both composition and space group was 74%, indicating solid performance and highlighting the model's effectiveness in handling complex generation criteria. Figure provides a visual comparison between ground-truth and generated structures across various crystal systems, demonstrating the model's versatility. The visualizations include examples from cubic, hexagonal, trigonal, tetragonal, orthorhombic, monoclinic, and triclinic systems. By showcasing these diverse structures, the figure highlights the model's ability to accurately generate crystal structures across a wide range of symmetries and compositions.