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updated classification and STS result

README.md

@@ -19,6 +19,103 @@ model-index:
       value: 39.50276109614102
     - type: f1
       value: 70.00224623431103
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 91.013675
+    - type: ap
+      value: 87.30227544778319
+    - type: f1
+      value: 91.00157923673694
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 46.986000000000004
+    - type: f1
+      value: 44.93316837240337
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.521
+    - type: map_at_10
+      value: 45.062999999999995
+    - type: map_at_100
+      value: 45.965
+    - type: map_at_1000
+      value: 45.972
+    - type: map_at_3
+      value: 40.078
+    - type: map_at_5
+      value: 43.158
+    - type: mrr_at_1
+      value: 29.232000000000003
+    - type: mrr_at_10
+      value: 45.305
+    - type: mrr_at_100
+      value: 46.213
+    - type: mrr_at_1000
+      value: 46.22
+    - type: mrr_at_3
+      value: 40.339000000000006
+    - type: mrr_at_5
+      value: 43.394
+    - type: ndcg_at_1
+      value: 28.521
+    - type: ndcg_at_10
+      value: 53.959999999999994
+    - type: ndcg_at_100
+      value: 57.691
+    - type: ndcg_at_1000
+      value: 57.858
+    - type: ndcg_at_3
+      value: 43.867
+    - type: ndcg_at_5
+      value: 49.38
+    - type: precision_at_1
+      value: 28.521
+    - type: precision_at_10
+      value: 8.222
+    - type: precision_at_100
+      value: 0.9820000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 18.279
+    - type: precision_at_5
+      value: 13.627
+    - type: recall_at_1
+      value: 28.521
+    - type: recall_at_10
+      value: 82.219
+    - type: recall_at_100
+      value: 98.222
+    - type: recall_at_1000
+      value: 99.502
+    - type: recall_at_3
+      value: 54.836
+    - type: recall_at_5
+      value: 68.137
   - task:
       type: Clustering
     dataset:
@@ -77,6 +174,75 @@ model-index:
       value: 81.93181818181819
     - type: f1
       value: 81.0852312152688
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.784
+    - type: map_at_10
+      value: 38.879000000000005
+    - type: map_at_100
+      value: 40.161
+    - type: map_at_1000
+      value: 40.291
+    - type: map_at_3
+      value: 36.104
+    - type: map_at_5
+      value: 37.671
+    - type: mrr_at_1
+      value: 35.924
+    - type: mrr_at_10
+      value: 44.471
+    - type: mrr_at_100
+      value: 45.251000000000005
+    - type: mrr_at_1000
+      value: 45.296
+    - type: mrr_at_3
+      value: 42.367
+    - type: mrr_at_5
+      value: 43.635000000000005
+    - type: ndcg_at_1
+      value: 35.924
+    - type: ndcg_at_10
+      value: 44.369
+    - type: ndcg_at_100
+      value: 48.925999999999995
+    - type: ndcg_at_1000
+      value: 50.964
+    - type: ndcg_at_3
+      value: 40.416999999999994
+    - type: ndcg_at_5
+      value: 42.309999999999995
+    - type: precision_at_1
+      value: 35.924
+    - type: precision_at_10
+      value: 8.344
+    - type: precision_at_100
+      value: 1.367
+    - type: precision_at_1000
+      value: 0.181
+    - type: precision_at_3
+      value: 19.469
+    - type: precision_at_5
+      value: 13.771
+    - type: recall_at_1
+      value: 28.784
+    - type: recall_at_10
+      value: 53.92400000000001
+    - type: recall_at_100
+      value: 72.962
+    - type: recall_at_1000
+      value: 85.90100000000001
+    - type: recall_at_3
+      value: 42.574
+    - type: recall_at_5
+      value: 47.798
   - task:
       type: Classification
     dataset:
@@ -90,6 +256,90 @@ model-index:
       value: 50.16499999999999
     - type: f1
       value: 43.57906972116264
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.737
+    - type: map_at_10
+      value: 33.566
+    - type: map_at_100
+      value: 35.367
+    - type: map_at_1000
+      value: 35.546
+    - type: map_at_3
+      value: 29.881999999999998
+    - type: map_at_5
+      value: 31.818
+    - type: mrr_at_1
+      value: 41.975
+    - type: mrr_at_10
+      value: 50.410999999999994
+    - type: mrr_at_100
+      value: 51.172
+    - type: mrr_at_1000
+      value: 51.214999999999996
+    - type: mrr_at_3
+      value: 48.611
+    - type: mrr_at_5
+      value: 49.522
+    - type: ndcg_at_1
+      value: 41.975
+    - type: ndcg_at_10
+      value: 41.299
+    - type: ndcg_at_100
+      value: 47.768
+    - type: ndcg_at_1000
+      value: 50.882000000000005
+    - type: ndcg_at_3
+      value: 38.769
+    - type: ndcg_at_5
+      value: 39.106
+    - type: precision_at_1
+      value: 41.975
+    - type: precision_at_10
+      value: 11.296000000000001
+    - type: precision_at_100
+      value: 1.7840000000000003
+    - type: precision_at_1000
+      value: 0.23500000000000001
+    - type: precision_at_3
+      value: 26.029000000000003
+    - type: precision_at_5
+      value: 18.457
+    - type: recall_at_1
+      value: 20.737
+    - type: recall_at_10
+      value: 47.284
+    - type: recall_at_100
+      value: 71.286
+    - type: recall_at_1000
+      value: 89.897
+    - type: recall_at_3
+      value: 35.411
+    - type: recall_at_5
+      value: 39.987
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 87.84
+    - type: ap
+      value: 82.68294664793142
+    - type: f1
+      value: 87.8226441992267
   - task:
       type: Classification
     dataset:
@@ -142,6 +392,75 @@ model-index:
       value: 76.63752521856087
     - type: f1
       value: 75.61348469613843
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.234
+    - type: map_at_10
+      value: 11.718
+    - type: map_at_100
+      value: 14.396
+    - type: map_at_1000
+      value: 15.661
+    - type: map_at_3
+      value: 8.951
+    - type: map_at_5
+      value: 10.233
+    - type: mrr_at_1
+      value: 43.034
+    - type: mrr_at_10
+      value: 52.161
+    - type: mrr_at_100
+      value: 52.729000000000006
+    - type: mrr_at_1000
+      value: 52.776
+    - type: mrr_at_3
+      value: 50.671
+    - type: mrr_at_5
+      value: 51.476
+    - type: ndcg_at_1
+      value: 41.331
+    - type: ndcg_at_10
+      value: 31.411
+    - type: ndcg_at_100
+      value: 28.459
+    - type: ndcg_at_1000
+      value: 37.114000000000004
+    - type: ndcg_at_3
+      value: 37.761
+    - type: ndcg_at_5
+      value: 35.118
+    - type: precision_at_1
+      value: 43.034
+    - type: precision_at_10
+      value: 22.878999999999998
+    - type: precision_at_100
+      value: 7.093000000000001
+    - type: precision_at_1000
+      value: 1.9560000000000002
+    - type: precision_at_3
+      value: 35.707
+    - type: precision_at_5
+      value: 30.279
+    - type: recall_at_1
+      value: 5.234
+    - type: recall_at_10
+      value: 14.745
+    - type: recall_at_100
+      value: 28.259
+    - type: recall_at_1000
+      value: 59.16400000000001
+    - type: recall_at_3
+      value: 10.08
+    - type: recall_at_5
+      value: 11.985
   - task:
       type: STS
     dataset:
@@ -310,6 +629,75 @@ model-index:
       value: 84.31171573973266
     - type: manhattan_spearman
       value: 84.79550448196474
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 48.178
+    - type: map_at_10
+      value: 59.24
+    - type: map_at_100
+      value: 59.902
+    - type: map_at_1000
+      value: 59.941
+    - type: map_at_3
+      value: 56.999
+    - type: map_at_5
+      value: 58.167
+    - type: mrr_at_1
+      value: 51.0
+    - type: mrr_at_10
+      value: 60.827
+    - type: mrr_at_100
+      value: 61.307
+    - type: mrr_at_1000
+      value: 61.341
+    - type: mrr_at_3
+      value: 59.0
+    - type: mrr_at_5
+      value: 60.033
+    - type: ndcg_at_1
+      value: 51.0
+    - type: ndcg_at_10
+      value: 64.366
+    - type: ndcg_at_100
+      value: 67.098
+    - type: ndcg_at_1000
+      value: 68.08
+    - type: ndcg_at_3
+      value: 60.409
+    - type: ndcg_at_5
+      value: 62.150000000000006
+    - type: precision_at_1
+      value: 51.0
+    - type: precision_at_10
+      value: 8.799999999999999
+    - type: precision_at_100
+      value: 1.027
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 24.444
+    - type: precision_at_5
+      value: 15.8
+    - type: recall_at_1
+      value: 48.178
+    - type: recall_at_10
+      value: 78.34400000000001
+    - type: recall_at_100
+      value: 90.36699999999999
+    - type: recall_at_1000
+      value: 98.0
+    - type: recall_at_3
+      value: 67.35
+    - type: recall_at_5
+      value: 71.989
   - task:
       type: PairClassification
     dataset: