Update README.md

README.md

@@ -20,6 +20,30 @@ model-index:
     metrics:
     - type: v_measure
       value: 59.14629497199997
+  - task:
+      type: Clustering
+    dataset:
+      type: lyon-nlp/alloprof
+      name: MTEB AlloProfClusteringS2S
+      config: default
+      split: test
+      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
+    metrics:
+    - type: v_measure
+      value: 36.450870830351036
+  - task:
+      type: Reranking
+    dataset:
+      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
+      name: MTEB AlloprofReranking
+      config: default
+      split: test
+      revision: e40c8a63ce02da43200eccb5b0846fcaa888f562
+    metrics:
+    - type: map
+      value: 67.23549444979429
+    - type: mrr
+      value: 68.49382830276612
   - task:
       type: Retrieval
     dataset:
@@ -27,92 +51,68 @@ model-index:
       name: MTEB AlloprofRetrieval
       config: default
       split: test
-      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
+      revision: 2df7bee4080bedf2e97de3da6bd5c7bc9fc9c4d2
     metrics:
     - type: map_at_1
-      value: 30.19
+      value: 30.285
     - type: map_at_10
-      value: 41.709
+      value: 41.724
     - type: map_at_100
-      value: 42.693
+      value: 42.696
     - type: map_at_1000
-      value: 42.735
+      value: 42.739
     - type: map_at_3
-      value: 38.651
+      value: 38.68
     - type: map_at_5
-      value: 40.498
+      value: 40.474
     - type: mrr_at_1
-      value: 30.19
+      value: 30.285
     - type: mrr_at_10
-      value: 41.709
+      value: 41.724
     - type: mrr_at_100
-      value: 42.693
+      value: 42.696
     - type: mrr_at_1000
-      value: 42.735
+      value: 42.739
     - type: mrr_at_3
-      value: 38.651
+      value: 38.68
     - type: mrr_at_5
-      value: 40.498
+      value: 40.474
     - type: ndcg_at_1
-      value: 30.19
+      value: 30.285
     - type: ndcg_at_10
-      value: 47.663
+      value: 47.687000000000005
     - type: ndcg_at_100
-      value: 52.586999999999996
+      value: 52.580000000000005
     - type: ndcg_at_1000
-      value: 53.727000000000004
+      value: 53.738
     - type: ndcg_at_3
-      value: 41.425
+      value: 41.439
     - type: ndcg_at_5
-      value: 44.746
+      value: 44.67
     - type: precision_at_1
-      value: 30.19
+      value: 30.285
     - type: precision_at_10
-      value: 6.648999999999999
+      value: 6.657
     - type: precision_at_100
       value: 0.898
     - type: precision_at_1000
       value: 0.099
     - type: precision_at_3
-      value: 16.485
+      value: 16.477
     - type: precision_at_5
-      value: 11.501
+      value: 11.454
     - type: recall_at_1
-      value: 30.19
+      value: 30.285
     - type: recall_at_10
-      value: 66.485
+      value: 66.572
     - type: recall_at_100
-      value: 89.81
+      value: 89.819
     - type: recall_at_1000
-      value: 98.80799999999999
+      value: 98.955
     - type: recall_at_3
-      value: 49.456
+      value: 49.43
     - type: recall_at_5
-      value: 57.504
-  - task:
-      type: Clustering
-    dataset:
-      type: lyon-nlp/alloprof
-      name: MTEB AlloProfClusteringS2S
-      config: default
-      split: test
-      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
-    metrics:
-    - type: v_measure
-      value: 36.450870830351036
-  - task:
-      type: Reranking
-    dataset:
-      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
-      name: MTEB AlloprofReranking
-      config: default
-      split: test
-      revision: e40c8a63ce02da43200eccb5b0846fcaa888f562
-    metrics:
-    - type: map
-      value: 67.23549444979429
-    - type: mrr
-      value: 68.49382830276612
+      value: 57.27100000000001
   - task:
       type: Classification
     dataset:
@@ -384,6 +384,61 @@ model-index:
       value: 28.500999999999998
     - type: recall_at_5
       value: 34.439
+  - task:
+      type: PairClassification
+    dataset:
+      type: GEM/opusparcus
+      name: MTEB OpusparcusPC (fr)
+      config: fr
+      split: test
+      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
+    metrics:
+    - type: cos_sim_accuracy
+      value: 82.56130790190736
+    - type: cos_sim_ap
+      value: 93.47537508242819
+    - type: cos_sim_f1
+      value: 87.60250844187169
+    - type: cos_sim_precision
+      value: 85.17823639774859
+    - type: cos_sim_recall
+      value: 90.16881827209534
+    - type: dot_accuracy
+      value: 81.06267029972753
+    - type: dot_ap
+      value: 91.67254760894009
+    - type: dot_f1
+      value: 87.07172224760164
+    - type: dot_precision
+      value: 80.62605752961083
+    - type: dot_recall
+      value: 94.63753723932473
+    - type: euclidean_accuracy
+      value: 81.19891008174388
+    - type: euclidean_ap
+      value: 93.11746326702661
+    - type: euclidean_f1
+      value: 86.52278177458035
+    - type: euclidean_precision
+      value: 83.6734693877551
+    - type: euclidean_recall
+      value: 89.57298907646475
+    - type: manhattan_accuracy
+      value: 81.06267029972753
+    - type: manhattan_ap
+      value: 93.10511956552851
+    - type: manhattan_f1
+      value: 86.62175168431185
+    - type: manhattan_precision
+      value: 84.03361344537815
+    - type: manhattan_recall
+      value: 89.37437934458788
+    - type: max_accuracy
+      value: 82.56130790190736
+    - type: max_ap
+      value: 93.47537508242819
+    - type: max_f1
+      value: 87.60250844187169
   - task:
       type: PairClassification
     dataset: