| import pandas as pd, os | |
| models = { | |
| 'DistilBERT': 'D:/SVD_Project/results/distilbert_final_sweep/summary.csv', | |
| 'RoBERTa': 'D:/SVD_Project/results/roberta_final_sweep/summary.csv', | |
| 'GPT-2': 'D:/SVD_Project/results/gpt2_final_sweep/summary.csv', | |
| 'Qwen3.5': 'D:/SVD_Project/results/qwen3_5_final_sweep/summary.csv', | |
| } | |
| print("=" * 70) | |
| print(" adaptive_span in existing final sweeps") | |
| print("=" * 70) | |
| for m, p in models.items(): | |
| p = p.replace('/', os.sep) | |
| if os.path.exists(p): | |
| df = pd.read_csv(p) | |
| row = df[df['module_name'].str.contains('adaptive_span', case=False, na=False)] | |
| if not row.empty: | |
| print(f"{m}: {row[['module_name','status','accuracy_pct']].to_string(index=False)}") | |
| else: | |
| print(f"{m}: NO adaptive_span row in summary.csv ({len(df)} total rows)") | |
| else: | |
| print(f"{m}: summary.csv NOT FOUND at {p}") | |
Xet Storage Details
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