| 2023-06-18 22:30:23 - Load pretrained SentenceTransformer: /kaggle/working/output/msmarco-bert-base-dot-v5-v2-Titles-wiht_150000_samples | |
| 2023-06-18 22:30:27 - Use pytorch device: cuda | |
| 2023-06-18 22:30:27 - Information Retrieval Evaluation on msmarco-bert-base-dot-v5 dataset: | |
| 2023-06-18 22:56:13 - Queries: 22500 | |
| 2023-06-18 22:56:13 - Corpus: 150000 | |
| 2023-06-18 22:56:32 - Score-Function: dot_score | |
| 2023-06-18 22:56:32 - Accuracy@1: 65.53% | |
| 2023-06-18 22:56:32 - Accuracy@3: 79.30% | |
| 2023-06-18 22:56:32 - Accuracy@5: 83.45% | |
| 2023-06-18 22:56:32 - Accuracy@10: 87.78% | |
| 2023-06-18 22:56:32 - Accuracy@100: 96.06% | |
| 2023-06-18 22:56:32 - Precision@1: 65.53% | |
| 2023-06-18 22:56:32 - Precision@3: 26.43% | |
| 2023-06-18 22:56:32 - Precision@5: 16.69% | |
| 2023-06-18 22:56:32 - Precision@10: 8.78% | |
| 2023-06-18 22:56:32 - Precision@100: 0.96% | |
| 2023-06-18 22:56:32 - Recall@1: 65.53% | |
| 2023-06-18 22:56:32 - Recall@3: 79.30% | |
| 2023-06-18 22:56:32 - Recall@5: 83.45% | |
| 2023-06-18 22:56:32 - Recall@10: 87.78% | |
| 2023-06-18 22:56:32 - Recall@100: 96.06% | |
| 2023-06-18 22:56:32 - MRR@1: 0.6553 | |
| 2023-06-18 22:56:32 - MRR@10: 0.7327 | |
| 2023-06-18 22:56:32 - MRR@100: 0.7364 | |
| 2023-06-18 22:56:32 - NDCG@1: 0.6553 | |
| 2023-06-18 22:56:32 - NDCG@10: 0.7680 | |
| 2023-06-18 22:56:32 - NDCG@100: 0.7858 | |
| 2023-06-18 22:56:32 - MAP@1: 0.6553 | |
| 2023-06-18 22:56:32 - MAP@10: 0.7327 | |
| 2023-06-18 22:56:32 - MAP@100: 0.7364 | |