Update README.md
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README.md
CHANGED
@@ -2601,6 +2601,1055 @@ model-index:
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value: 86.60631843011362
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- type: max_f1
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value: 79.14949970570925
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|
2604 |
---
|
2605 |
|
2606 |
## gte-Qwen2-7B-instruct
|
|
|
2601 |
value: 86.60631843011362
|
2602 |
- type: max_f1
|
2603 |
value: 79.14949970570925
|
2604 |
+
- task:
|
2605 |
+
type: STS
|
2606 |
+
dataset:
|
2607 |
+
type: C-MTEB/AFQMC
|
2608 |
+
name: MTEB AFQMC
|
2609 |
+
config: default
|
2610 |
+
split: validation
|
2611 |
+
revision: b44c3b011063adb25877c13823db83bb193913c4
|
2612 |
+
metrics:
|
2613 |
+
- type: cos_sim_pearson
|
2614 |
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value: 65.58442135663871
|
2615 |
+
- type: cos_sim_spearman
|
2616 |
+
value: 72.2538631361313
|
2617 |
+
- type: euclidean_pearson
|
2618 |
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value: 70.97255486607429
|
2619 |
+
- type: euclidean_spearman
|
2620 |
+
value: 72.25374250228647
|
2621 |
+
- type: manhattan_pearson
|
2622 |
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value: 70.83250199989911
|
2623 |
+
- type: manhattan_spearman
|
2624 |
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value: 72.14819496536272
|
2625 |
+
- task:
|
2626 |
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type: STS
|
2627 |
+
dataset:
|
2628 |
+
type: C-MTEB/ATEC
|
2629 |
+
name: MTEB ATEC
|
2630 |
+
config: default
|
2631 |
+
split: test
|
2632 |
+
revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
|
2633 |
+
metrics:
|
2634 |
+
- type: cos_sim_pearson
|
2635 |
+
value: 59.99478404929932
|
2636 |
+
- type: cos_sim_spearman
|
2637 |
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value: 62.61836216999812
|
2638 |
+
- type: euclidean_pearson
|
2639 |
+
value: 66.86429811933593
|
2640 |
+
- type: euclidean_spearman
|
2641 |
+
value: 62.6183520374191
|
2642 |
+
- type: manhattan_pearson
|
2643 |
+
value: 66.8063778911633
|
2644 |
+
- type: manhattan_spearman
|
2645 |
+
value: 62.569607573241115
|
2646 |
+
- task:
|
2647 |
+
type: Classification
|
2648 |
+
dataset:
|
2649 |
+
type: mteb/amazon_reviews_multi
|
2650 |
+
name: MTEB AmazonReviewsClassification (zh)
|
2651 |
+
config: zh
|
2652 |
+
split: test
|
2653 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
2654 |
+
metrics:
|
2655 |
+
- type: accuracy
|
2656 |
+
value: 53.98400000000001
|
2657 |
+
- type: f1
|
2658 |
+
value: 51.21447361350723
|
2659 |
+
- task:
|
2660 |
+
type: STS
|
2661 |
+
dataset:
|
2662 |
+
type: C-MTEB/BQ
|
2663 |
+
name: MTEB BQ
|
2664 |
+
config: default
|
2665 |
+
split: test
|
2666 |
+
revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
|
2667 |
+
metrics:
|
2668 |
+
- type: cos_sim_pearson
|
2669 |
+
value: 79.11941660686553
|
2670 |
+
- type: cos_sim_spearman
|
2671 |
+
value: 81.25029594540435
|
2672 |
+
- type: euclidean_pearson
|
2673 |
+
value: 82.06973504238826
|
2674 |
+
- type: euclidean_spearman
|
2675 |
+
value: 81.2501989488524
|
2676 |
+
- type: manhattan_pearson
|
2677 |
+
value: 82.10094630392753
|
2678 |
+
- type: manhattan_spearman
|
2679 |
+
value: 81.27987244392389
|
2680 |
+
- task:
|
2681 |
+
type: Clustering
|
2682 |
+
dataset:
|
2683 |
+
type: C-MTEB/CLSClusteringP2P
|
2684 |
+
name: MTEB CLSClusteringP2P
|
2685 |
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config: default
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2686 |
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split: test
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2687 |
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revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
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2688 |
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metrics:
|
2689 |
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- type: v_measure
|
2690 |
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value: 47.07270168705156
|
2691 |
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- task:
|
2692 |
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type: Clustering
|
2693 |
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dataset:
|
2694 |
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type: C-MTEB/CLSClusteringS2S
|
2695 |
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name: MTEB CLSClusteringS2S
|
2696 |
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config: default
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2697 |
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split: test
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2698 |
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2699 |
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metrics:
|
2700 |
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- type: v_measure
|
2701 |
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value: 45.98511703185043
|
2702 |
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- task:
|
2703 |
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type: Reranking
|
2704 |
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dataset:
|
2705 |
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type: C-MTEB/CMedQAv1-reranking
|
2706 |
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name: MTEB CMedQAv1
|
2707 |
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config: default
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2708 |
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split: test
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2709 |
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revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
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2710 |
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metrics:
|
2711 |
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- type: map
|
2712 |
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value: 88.19895157194931
|
2713 |
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- type: mrr
|
2714 |
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value: 90.21424603174603
|
2715 |
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- task:
|
2716 |
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type: Reranking
|
2717 |
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dataset:
|
2718 |
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type: C-MTEB/CMedQAv2-reranking
|
2719 |
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name: MTEB CMedQAv2
|
2720 |
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config: default
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2721 |
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split: test
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2722 |
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revision: 23d186750531a14a0357ca22cd92d712fd512ea0
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2723 |
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metrics:
|
2724 |
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- type: map
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2725 |
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2726 |
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- type: mrr
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2727 |
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|
2728 |
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- task:
|
2729 |
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type: Retrieval
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2730 |
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dataset:
|
2731 |
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type: C-MTEB/CmedqaRetrieval
|
2732 |
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name: MTEB CmedqaRetrieval
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2733 |
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2734 |
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split: dev
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2735 |
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revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
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2736 |
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metrics:
|
2737 |
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2738 |
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value: 29.037000000000003
|
2739 |
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- type: map_at_10
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2740 |
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2741 |
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- type: map_at_100
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2742 |
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value: 43.773
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2743 |
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- type: map_at_1000
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2744 |
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2745 |
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- type: map_at_3
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2746 |
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2747 |
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- type: map_at_5
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2748 |
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value: 40.034
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2749 |
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- type: mrr_at_1
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2750 |
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2751 |
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- type: mrr_at_10
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2752 |
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value: 51.158
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2753 |
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- type: mrr_at_100
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2754 |
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2755 |
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- type: mrr_at_1000
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2756 |
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2757 |
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- type: mrr_at_3
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2758 |
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2759 |
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- type: mrr_at_5
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2760 |
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2761 |
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- type: ndcg_at_1
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2762 |
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2763 |
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2764 |
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2765 |
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- type: ndcg_at_100
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2766 |
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value: 55.513
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2767 |
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- type: ndcg_at_1000
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2768 |
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2769 |
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- type: ndcg_at_3
|
2770 |
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value: 43.329
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2771 |
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- type: ndcg_at_5
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2772 |
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value: 45.438
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2773 |
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- type: precision_at_1
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2774 |
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value: 43.136
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2775 |
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- type: precision_at_10
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2776 |
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value: 10.56
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2777 |
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- type: precision_at_100
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2778 |
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value: 1.6129999999999998
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2779 |
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- type: precision_at_1000
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2780 |
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value: 0.184
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2781 |
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- type: precision_at_3
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2782 |
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value: 24.064
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2783 |
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- type: precision_at_5
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2784 |
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value: 17.269000000000002
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2785 |
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- type: recall_at_1
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2786 |
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value: 29.037000000000003
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2787 |
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- type: recall_at_10
|
2788 |
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2789 |
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- type: recall_at_100
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2790 |
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value: 87.355
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2791 |
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- type: recall_at_1000
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2792 |
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value: 98.74000000000001
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2793 |
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- type: recall_at_3
|
2794 |
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value: 42.99
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2795 |
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- type: recall_at_5
|
2796 |
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value: 49.681999999999995
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2797 |
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- task:
|
2798 |
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type: PairClassification
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2799 |
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dataset:
|
2800 |
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type: C-MTEB/CMNLI
|
2801 |
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name: MTEB Cmnli
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2802 |
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config: default
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2803 |
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split: validation
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2804 |
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revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
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2805 |
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metrics:
|
2806 |
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- type: cos_sim_accuracy
|
2807 |
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value: 82.68190018039687
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2808 |
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- type: cos_sim_ap
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2809 |
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2810 |
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- type: cos_sim_f1
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2811 |
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2812 |
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- type: cos_sim_precision
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2813 |
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2814 |
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- type: cos_sim_recall
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2815 |
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2816 |
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- type: dot_accuracy
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2817 |
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2818 |
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- type: dot_ap
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2819 |
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2820 |
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- type: dot_f1
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2821 |
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2822 |
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- type: dot_precision
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2823 |
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|
2824 |
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- type: dot_recall
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2825 |
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value: 88.05237315875614
|
2826 |
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- type: euclidean_accuracy
|
2827 |
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2828 |
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- type: euclidean_ap
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2829 |
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2830 |
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- type: euclidean_f1
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2831 |
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value: 83.63636363636364
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2832 |
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- type: euclidean_precision
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2833 |
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value: 79.52772506852203
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2834 |
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- type: euclidean_recall
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2835 |
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value: 88.19265840542437
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2836 |
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- type: manhattan_accuracy
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2837 |
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value: 82.14070956103427
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2838 |
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- type: manhattan_ap
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2839 |
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2840 |
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- type: manhattan_f1
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2842 |
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- type: manhattan_precision
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value: 78.35605121850475
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2844 |
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- type: manhattan_recall
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2846 |
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- type: max_accuracy
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2847 |
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2848 |
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- type: max_ap
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2849 |
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2850 |
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- type: max_f1
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2851 |
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2852 |
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- task:
|
2853 |
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type: Retrieval
|
2854 |
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dataset:
|
2855 |
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type: C-MTEB/CovidRetrieval
|
2856 |
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name: MTEB CovidRetrieval
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2857 |
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config: default
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2858 |
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split: dev
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2859 |
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revision: 1271c7809071a13532e05f25fb53511ffce77117
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2860 |
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metrics:
|
2861 |
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- type: map_at_1
|
2862 |
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value: 72.234
|
2863 |
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- type: map_at_10
|
2864 |
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value: 80.10000000000001
|
2865 |
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- type: map_at_100
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2866 |
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value: 80.36
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2867 |
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- type: map_at_1000
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2868 |
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value: 80.363
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2869 |
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- type: map_at_3
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2870 |
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value: 78.315
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2871 |
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- type: map_at_5
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2872 |
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value: 79.607
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2873 |
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- type: mrr_at_1
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2874 |
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value: 72.392
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2875 |
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- type: mrr_at_10
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2876 |
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value: 80.117
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2877 |
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- type: mrr_at_100
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2878 |
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value: 80.36999999999999
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2879 |
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- type: mrr_at_1000
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2880 |
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value: 80.373
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2881 |
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- type: mrr_at_3
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2882 |
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value: 78.469
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2883 |
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- type: mrr_at_5
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2884 |
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2885 |
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- type: ndcg_at_1
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2886 |
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2887 |
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- type: ndcg_at_10
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2888 |
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value: 83.651
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2889 |
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- type: ndcg_at_100
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2890 |
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|
2891 |
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- type: ndcg_at_1000
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2892 |
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value: 84.83000000000001
|
2893 |
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- type: ndcg_at_3
|
2894 |
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value: 80.253
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2895 |
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- type: ndcg_at_5
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2896 |
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value: 82.485
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2897 |
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- type: precision_at_1
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2898 |
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value: 72.392
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2899 |
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- type: precision_at_10
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2900 |
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value: 9.557
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2901 |
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- type: precision_at_100
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2902 |
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value: 1.004
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2903 |
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- type: precision_at_1000
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2904 |
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value: 0.101
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2905 |
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- type: precision_at_3
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2906 |
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value: 28.732000000000003
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2907 |
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- type: precision_at_5
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2908 |
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value: 18.377
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2909 |
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- type: recall_at_1
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2910 |
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value: 72.234
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2911 |
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- type: recall_at_10
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2912 |
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value: 94.573
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2913 |
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- type: recall_at_100
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2914 |
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value: 99.368
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2915 |
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- type: recall_at_1000
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2916 |
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value: 100.0
|
2917 |
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- type: recall_at_3
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2918 |
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value: 85.669
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2919 |
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- type: recall_at_5
|
2920 |
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value: 91.01700000000001
|
2921 |
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- task:
|
2922 |
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type: Retrieval
|
2923 |
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dataset:
|
2924 |
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type: C-MTEB/DuRetrieval
|
2925 |
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name: MTEB DuRetrieval
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2926 |
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config: default
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2927 |
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split: dev
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2928 |
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revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
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2929 |
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metrics:
|
2930 |
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- type: map_at_1
|
2931 |
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value: 26.173999999999996
|
2932 |
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- type: map_at_10
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2933 |
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2934 |
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- type: map_at_100
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2935 |
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2936 |
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2937 |
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2938 |
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2939 |
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2940 |
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- type: map_at_5
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2941 |
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value: 69.89800000000001
|
2942 |
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- type: mrr_at_1
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2943 |
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value: 89.5
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2944 |
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- type: mrr_at_10
|
2945 |
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value: 92.996
|
2946 |
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- type: mrr_at_100
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2947 |
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value: 93.06400000000001
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2948 |
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- type: mrr_at_1000
|
2949 |
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value: 93.065
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2950 |
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- type: mrr_at_3
|
2951 |
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value: 92.658
|
2952 |
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- type: mrr_at_5
|
2953 |
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|
2954 |
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- type: ndcg_at_1
|
2955 |
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|
2956 |
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- type: ndcg_at_10
|
2957 |
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value: 87.443
|
2958 |
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- type: ndcg_at_100
|
2959 |
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|
2960 |
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- type: ndcg_at_1000
|
2961 |
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value: 90.549
|
2962 |
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- type: ndcg_at_3
|
2963 |
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value: 85.874
|
2964 |
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- type: ndcg_at_5
|
2965 |
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value: 84.842
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2966 |
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- type: precision_at_1
|
2967 |
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value: 89.5
|
2968 |
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- type: precision_at_10
|
2969 |
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value: 41.805
|
2970 |
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- type: precision_at_100
|
2971 |
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value: 4.827
|
2972 |
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- type: precision_at_1000
|
2973 |
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value: 0.49
|
2974 |
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- type: precision_at_3
|
2975 |
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value: 76.85
|
2976 |
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- type: precision_at_5
|
2977 |
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value: 64.8
|
2978 |
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- type: recall_at_1
|
2979 |
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value: 26.173999999999996
|
2980 |
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- type: recall_at_10
|
2981 |
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value: 89.101
|
2982 |
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- type: recall_at_100
|
2983 |
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value: 98.08099999999999
|
2984 |
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- type: recall_at_1000
|
2985 |
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value: 99.529
|
2986 |
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- type: recall_at_3
|
2987 |
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value: 57.902
|
2988 |
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- type: recall_at_5
|
2989 |
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value: 74.602
|
2990 |
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- task:
|
2991 |
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type: Retrieval
|
2992 |
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dataset:
|
2993 |
+
type: C-MTEB/EcomRetrieval
|
2994 |
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name: MTEB EcomRetrieval
|
2995 |
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config: default
|
2996 |
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split: dev
|
2997 |
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revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
|
2998 |
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metrics:
|
2999 |
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- type: map_at_1
|
3000 |
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value: 56.10000000000001
|
3001 |
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- type: map_at_10
|
3002 |
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|
3003 |
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- type: map_at_100
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3004 |
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3005 |
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- type: map_at_1000
|
3006 |
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value: 66.636
|
3007 |
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|
3008 |
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|
3009 |
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- type: map_at_5
|
3010 |
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value: 65.293
|
3011 |
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- type: mrr_at_1
|
3012 |
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|
3013 |
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- type: mrr_at_10
|
3014 |
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|
3015 |
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- type: mrr_at_100
|
3016 |
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value: 66.625
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3017 |
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- type: mrr_at_1000
|
3018 |
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|
3019 |
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- type: mrr_at_3
|
3020 |
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|
3021 |
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- type: mrr_at_5
|
3022 |
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|
3023 |
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- type: ndcg_at_1
|
3024 |
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|
3025 |
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- type: ndcg_at_10
|
3026 |
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value: 71.146
|
3027 |
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- type: ndcg_at_100
|
3028 |
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|
3029 |
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- type: ndcg_at_1000
|
3030 |
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|
3031 |
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- type: ndcg_at_3
|
3032 |
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value: 66.09
|
3033 |
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- type: ndcg_at_5
|
3034 |
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|
3035 |
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- type: precision_at_1
|
3036 |
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value: 56.10000000000001
|
3037 |
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- type: precision_at_10
|
3038 |
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value: 8.68
|
3039 |
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- type: precision_at_100
|
3040 |
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value: 0.964
|
3041 |
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- type: precision_at_1000
|
3042 |
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value: 0.098
|
3043 |
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- type: precision_at_3
|
3044 |
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value: 24.4
|
3045 |
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- type: precision_at_5
|
3046 |
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value: 16.1
|
3047 |
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- type: recall_at_1
|
3048 |
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value: 56.10000000000001
|
3049 |
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- type: recall_at_10
|
3050 |
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value: 86.8
|
3051 |
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- type: recall_at_100
|
3052 |
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value: 96.39999999999999
|
3053 |
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- type: recall_at_1000
|
3054 |
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value: 98.3
|
3055 |
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- type: recall_at_3
|
3056 |
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value: 73.2
|
3057 |
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- type: recall_at_5
|
3058 |
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value: 80.5
|
3059 |
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- task:
|
3060 |
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type: Classification
|
3061 |
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dataset:
|
3062 |
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type: C-MTEB/IFlyTek-classification
|
3063 |
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name: MTEB IFlyTek
|
3064 |
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config: default
|
3065 |
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split: validation
|
3066 |
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revision: 421605374b29664c5fc098418fe20ada9bd55f8a
|
3067 |
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metrics:
|
3068 |
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- type: accuracy
|
3069 |
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value: 54.52096960369373
|
3070 |
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- type: f1
|
3071 |
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value: 40.930845295808695
|
3072 |
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- task:
|
3073 |
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type: Classification
|
3074 |
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dataset:
|
3075 |
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type: C-MTEB/JDReview-classification
|
3076 |
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name: MTEB JDReview
|
3077 |
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config: default
|
3078 |
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split: test
|
3079 |
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|
3080 |
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metrics:
|
3081 |
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- type: accuracy
|
3082 |
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value: 86.51031894934334
|
3083 |
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- type: ap
|
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3085 |
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3086 |
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3087 |
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- task:
|
3088 |
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type: STS
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3089 |
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|
3090 |
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type: C-MTEB/LCQMC
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3091 |
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name: MTEB LCQMC
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3092 |
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config: default
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split: test
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|
3096 |
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3097 |
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value: 69.67437838574276
|
3098 |
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- type: euclidean_pearson
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3101 |
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- type: euclidean_spearman
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- type: manhattan_pearson
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- type: manhattan_spearman
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value: 73.7590419009179
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- task:
|
3109 |
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type: Reranking
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3110 |
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dataset:
|
3111 |
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type: C-MTEB/Mmarco-reranking
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3112 |
+
name: MTEB MMarcoReranking
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3113 |
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config: default
|
3114 |
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split: dev
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3115 |
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revision: None
|
3116 |
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metrics:
|
3117 |
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- type: map
|
3118 |
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value: 31.648613483640254
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3119 |
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- type: mrr
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3120 |
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3121 |
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- task:
|
3122 |
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type: Retrieval
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3123 |
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dataset:
|
3124 |
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type: C-MTEB/MMarcoRetrieval
|
3125 |
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name: MTEB MMarcoRetrieval
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3126 |
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config: default
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3127 |
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split: dev
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3130 |
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3131 |
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value: 73.28099999999999
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3132 |
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3133 |
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3135 |
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3139 |
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3141 |
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3142 |
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3143 |
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3159 |
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3162 |
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value: 1.052
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value: 86.984
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- type: recall_at_5
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3189 |
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value: 91.024
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3190 |
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- task:
|
3191 |
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type: Classification
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3192 |
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dataset:
|
3193 |
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type: mteb/amazon_massive_intent
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3194 |
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name: MTEB MassiveIntentClassification (zh-CN)
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split: test
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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3198 |
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metrics:
|
3199 |
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- type: accuracy
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3200 |
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3201 |
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- type: f1
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3202 |
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3203 |
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- task:
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3204 |
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type: Classification
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3205 |
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dataset:
|
3206 |
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type: mteb/amazon_massive_scenario
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3207 |
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name: MTEB MassiveScenarioClassification (zh-CN)
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3208 |
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config: zh-CN
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3209 |
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split: test
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3210 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
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3211 |
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metrics:
|
3212 |
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- type: accuracy
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3213 |
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3214 |
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- type: f1
|
3215 |
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value: 85.05279279434997
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3216 |
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- task:
|
3217 |
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type: Retrieval
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3218 |
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dataset:
|
3219 |
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type: C-MTEB/MedicalRetrieval
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3220 |
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name: MTEB MedicalRetrieval
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3221 |
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config: default
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3222 |
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split: dev
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3223 |
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revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
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3224 |
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metrics:
|
3225 |
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- type: map_at_1
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3226 |
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value: 56.2
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3227 |
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- type: map_at_10
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3228 |
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value: 62.57899999999999
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3229 |
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- type: map_at_100
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3230 |
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3231 |
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- type: map_at_1000
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3232 |
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3233 |
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- type: map_at_3
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3234 |
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value: 61.217
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3235 |
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3236 |
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3237 |
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- type: mrr_at_1
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3238 |
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3239 |
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3240 |
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3241 |
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3242 |
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3243 |
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- type: mrr_at_1000
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3244 |
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3245 |
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3246 |
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value: 61.267
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3247 |
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- type: mrr_at_5
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3248 |
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value: 62.062
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3249 |
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- type: ndcg_at_1
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3250 |
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value: 56.2
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3251 |
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- type: ndcg_at_10
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3252 |
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value: 65.592
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3253 |
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- type: ndcg_at_100
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3254 |
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value: 68.657
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3255 |
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- type: ndcg_at_1000
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3256 |
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value: 69.671
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3257 |
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- type: ndcg_at_3
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3258 |
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3259 |
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3260 |
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value: 64.24499999999999
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3261 |
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- type: precision_at_1
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3262 |
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value: 56.2
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3263 |
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- type: precision_at_10
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3264 |
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value: 7.5
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3265 |
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- type: precision_at_100
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3266 |
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value: 0.899
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3267 |
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- type: precision_at_1000
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3268 |
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value: 0.098
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3269 |
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- type: precision_at_3
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3270 |
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value: 22.467000000000002
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3271 |
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- type: precision_at_5
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3272 |
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value: 14.180000000000001
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3273 |
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- type: recall_at_1
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3274 |
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value: 56.2
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3275 |
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- type: recall_at_10
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3276 |
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value: 75.0
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3277 |
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- type: recall_at_100
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3278 |
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value: 89.9
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3279 |
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- type: recall_at_1000
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3280 |
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value: 97.89999999999999
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3281 |
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- type: recall_at_3
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3282 |
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value: 67.4
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3283 |
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- type: recall_at_5
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3284 |
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value: 70.89999999999999
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3285 |
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- task:
|
3286 |
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type: Classification
|
3287 |
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dataset:
|
3288 |
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type: C-MTEB/MultilingualSentiment-classification
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3289 |
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name: MTEB MultilingualSentiment
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3290 |
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config: default
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3291 |
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split: validation
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3292 |
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3293 |
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metrics:
|
3294 |
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- type: accuracy
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3295 |
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3296 |
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- type: f1
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3297 |
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3298 |
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- task:
|
3299 |
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type: PairClassification
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3300 |
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dataset:
|
3301 |
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type: C-MTEB/OCNLI
|
3302 |
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name: MTEB Ocnli
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3303 |
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config: default
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3304 |
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split: validation
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3305 |
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revision: 66e76a618a34d6d565d5538088562851e6daa7ec
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3306 |
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metrics:
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3307 |
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3308 |
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value: 79.64266377910124
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3309 |
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- type: cos_sim_ap
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3310 |
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3311 |
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3313 |
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3314 |
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3315 |
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- type: cos_sim_recall
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3317 |
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3320 |
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3323 |
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3325 |
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- type: dot_recall
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3326 |
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3327 |
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- type: euclidean_accuracy
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3328 |
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- type: euclidean_ap
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3330 |
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3331 |
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- type: euclidean_f1
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3333 |
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- type: euclidean_precision
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3334 |
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3335 |
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- type: euclidean_recall
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3337 |
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- type: manhattan_accuracy
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3341 |
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3343 |
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3344 |
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value: 76.24768946395564
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3345 |
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- type: manhattan_recall
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3346 |
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value: 87.11721224920802
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3347 |
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- type: max_accuracy
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3348 |
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3349 |
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3350 |
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3351 |
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- type: max_f1
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3352 |
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3353 |
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- task:
|
3354 |
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type: Classification
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3355 |
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dataset:
|
3356 |
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type: C-MTEB/OnlineShopping-classification
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3357 |
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name: MTEB OnlineShopping
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3358 |
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3359 |
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3360 |
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3361 |
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metrics:
|
3362 |
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- type: accuracy
|
3363 |
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value: 94.3
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3364 |
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3365 |
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3366 |
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3367 |
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3368 |
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- task:
|
3369 |
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type: STS
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3370 |
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dataset:
|
3371 |
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type: C-MTEB/PAWSX
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3372 |
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name: MTEB PAWSX
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3373 |
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3374 |
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split: test
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3375 |
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3376 |
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metrics:
|
3377 |
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3378 |
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3379 |
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3380 |
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3381 |
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3382 |
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3383 |
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3387 |
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3389 |
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- task:
|
3390 |
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3391 |
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dataset:
|
3392 |
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3393 |
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3394 |
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3397 |
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3399 |
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3400 |
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3401 |
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3402 |
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3403 |
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3404 |
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3405 |
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3406 |
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3410 |
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3411 |
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type: STS
|
3412 |
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dataset:
|
3413 |
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type: mteb/sts22-crosslingual-sts
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3414 |
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name: MTEB STS22 (zh)
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3415 |
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3416 |
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split: test
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3417 |
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3418 |
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3419 |
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3421 |
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3422 |
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3423 |
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3424 |
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3425 |
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3431 |
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3432 |
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3433 |
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dataset:
|
3434 |
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|
3435 |
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3436 |
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3437 |
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3439 |
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3440 |
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3442 |
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3446 |
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3452 |
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- task:
|
3453 |
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3454 |
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dataset:
|
3455 |
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|
3456 |
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name: MTEB T2Reranking
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3457 |
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3458 |
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split: dev
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3459 |
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3460 |
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metrics:
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3461 |
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3463 |
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- type: mrr
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3464 |
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3465 |
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- task:
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3466 |
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dataset:
|
3468 |
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|
3469 |
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name: MTEB T2Retrieval
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3470 |
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3471 |
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split: dev
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3472 |
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3473 |
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3474 |
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3476 |
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3477 |
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3478 |
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- type: map_at_100
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3479 |
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value: 84.504
|
3480 |
+
- type: map_at_1000
|
3481 |
+
value: 84.552
|
3482 |
+
- type: map_at_3
|
3483 |
+
value: 56.897
|
3484 |
+
- type: map_at_5
|
3485 |
+
value: 70.073
|
3486 |
+
- type: mrr_at_1
|
3487 |
+
value: 92.087
|
3488 |
+
- type: mrr_at_10
|
3489 |
+
value: 94.132
|
3490 |
+
- type: mrr_at_100
|
3491 |
+
value: 94.19800000000001
|
3492 |
+
- type: mrr_at_1000
|
3493 |
+
value: 94.19999999999999
|
3494 |
+
- type: mrr_at_3
|
3495 |
+
value: 93.78999999999999
|
3496 |
+
- type: mrr_at_5
|
3497 |
+
value: 94.002
|
3498 |
+
- type: ndcg_at_1
|
3499 |
+
value: 92.087
|
3500 |
+
- type: ndcg_at_10
|
3501 |
+
value: 87.734
|
3502 |
+
- type: ndcg_at_100
|
3503 |
+
value: 90.736
|
3504 |
+
- type: ndcg_at_1000
|
3505 |
+
value: 91.184
|
3506 |
+
- type: ndcg_at_3
|
3507 |
+
value: 88.78
|
3508 |
+
- type: ndcg_at_5
|
3509 |
+
value: 87.676
|
3510 |
+
- type: precision_at_1
|
3511 |
+
value: 92.087
|
3512 |
+
- type: precision_at_10
|
3513 |
+
value: 43.46
|
3514 |
+
- type: precision_at_100
|
3515 |
+
value: 5.07
|
3516 |
+
- type: precision_at_1000
|
3517 |
+
value: 0.518
|
3518 |
+
- type: precision_at_3
|
3519 |
+
value: 77.49000000000001
|
3520 |
+
- type: precision_at_5
|
3521 |
+
value: 65.194
|
3522 |
+
- type: recall_at_1
|
3523 |
+
value: 28.666999999999998
|
3524 |
+
- type: recall_at_10
|
3525 |
+
value: 86.632
|
3526 |
+
- type: recall_at_100
|
3527 |
+
value: 96.646
|
3528 |
+
- type: recall_at_1000
|
3529 |
+
value: 98.917
|
3530 |
+
- type: recall_at_3
|
3531 |
+
value: 58.333999999999996
|
3532 |
+
- type: recall_at_5
|
3533 |
+
value: 72.974
|
3534 |
+
- task:
|
3535 |
+
type: Classification
|
3536 |
+
dataset:
|
3537 |
+
type: C-MTEB/TNews-classification
|
3538 |
+
name: MTEB TNews
|
3539 |
+
config: default
|
3540 |
+
split: validation
|
3541 |
+
revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
|
3542 |
+
metrics:
|
3543 |
+
- type: accuracy
|
3544 |
+
value: 52.971999999999994
|
3545 |
+
- type: f1
|
3546 |
+
value: 50.2898280984929
|
3547 |
+
- task:
|
3548 |
+
type: Clustering
|
3549 |
+
dataset:
|
3550 |
+
type: C-MTEB/ThuNewsClusteringP2P
|
3551 |
+
name: MTEB ThuNewsClusteringP2P
|
3552 |
+
config: default
|
3553 |
+
split: test
|
3554 |
+
revision: 5798586b105c0434e4f0fe5e767abe619442cf93
|
3555 |
+
metrics:
|
3556 |
+
- type: v_measure
|
3557 |
+
value: 86.0797948663824
|
3558 |
+
- task:
|
3559 |
+
type: Clustering
|
3560 |
+
dataset:
|
3561 |
+
type: C-MTEB/ThuNewsClusteringS2S
|
3562 |
+
name: MTEB ThuNewsClusteringS2S
|
3563 |
+
config: default
|
3564 |
+
split: test
|
3565 |
+
revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
|
3566 |
+
metrics:
|
3567 |
+
- type: v_measure
|
3568 |
+
value: 85.10759092255017
|
3569 |
+
- task:
|
3570 |
+
type: Retrieval
|
3571 |
+
dataset:
|
3572 |
+
type: C-MTEB/VideoRetrieval
|
3573 |
+
name: MTEB VideoRetrieval
|
3574 |
+
config: default
|
3575 |
+
split: dev
|
3576 |
+
revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
|
3577 |
+
metrics:
|
3578 |
+
- type: map_at_1
|
3579 |
+
value: 65.60000000000001
|
3580 |
+
- type: map_at_10
|
3581 |
+
value: 74.773
|
3582 |
+
- type: map_at_100
|
3583 |
+
value: 75.128
|
3584 |
+
- type: map_at_1000
|
3585 |
+
value: 75.136
|
3586 |
+
- type: map_at_3
|
3587 |
+
value: 73.05
|
3588 |
+
- type: map_at_5
|
3589 |
+
value: 74.13499999999999
|
3590 |
+
- type: mrr_at_1
|
3591 |
+
value: 65.60000000000001
|
3592 |
+
- type: mrr_at_10
|
3593 |
+
value: 74.773
|
3594 |
+
- type: mrr_at_100
|
3595 |
+
value: 75.128
|
3596 |
+
- type: mrr_at_1000
|
3597 |
+
value: 75.136
|
3598 |
+
- type: mrr_at_3
|
3599 |
+
value: 73.05
|
3600 |
+
- type: mrr_at_5
|
3601 |
+
value: 74.13499999999999
|
3602 |
+
- type: ndcg_at_1
|
3603 |
+
value: 65.60000000000001
|
3604 |
+
- type: ndcg_at_10
|
3605 |
+
value: 78.84299999999999
|
3606 |
+
- type: ndcg_at_100
|
3607 |
+
value: 80.40899999999999
|
3608 |
+
- type: ndcg_at_1000
|
3609 |
+
value: 80.57
|
3610 |
+
- type: ndcg_at_3
|
3611 |
+
value: 75.40599999999999
|
3612 |
+
- type: ndcg_at_5
|
3613 |
+
value: 77.351
|
3614 |
+
- type: precision_at_1
|
3615 |
+
value: 65.60000000000001
|
3616 |
+
- type: precision_at_10
|
3617 |
+
value: 9.139999999999999
|
3618 |
+
- type: precision_at_100
|
3619 |
+
value: 0.984
|
3620 |
+
- type: precision_at_1000
|
3621 |
+
value: 0.1
|
3622 |
+
- type: precision_at_3
|
3623 |
+
value: 27.400000000000002
|
3624 |
+
- type: precision_at_5
|
3625 |
+
value: 17.380000000000003
|
3626 |
+
- type: recall_at_1
|
3627 |
+
value: 65.60000000000001
|
3628 |
+
- type: recall_at_10
|
3629 |
+
value: 91.4
|
3630 |
+
- type: recall_at_100
|
3631 |
+
value: 98.4
|
3632 |
+
- type: recall_at_1000
|
3633 |
+
value: 99.6
|
3634 |
+
- type: recall_at_3
|
3635 |
+
value: 82.19999999999999
|
3636 |
+
- type: recall_at_5
|
3637 |
+
value: 86.9
|
3638 |
+
- task:
|
3639 |
+
type: Classification
|
3640 |
+
dataset:
|
3641 |
+
type: C-MTEB/waimai-classification
|
3642 |
+
name: MTEB Waimai
|
3643 |
+
config: default
|
3644 |
+
split: test
|
3645 |
+
revision: 339287def212450dcaa9df8c22bf93e9980c7023
|
3646 |
+
metrics:
|
3647 |
+
- type: accuracy
|
3648 |
+
value: 89.47
|
3649 |
+
- type: ap
|
3650 |
+
value: 75.59561751845389
|
3651 |
+
- type: f1
|
3652 |
+
value: 87.95207751382563
|
3653 |
---
|
3654 |
|
3655 |
## gte-Qwen2-7B-instruct
|