multi-train commited on
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1 Parent(s): 0afe5b5

Update README.md

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  1. README.md +11 -12
README.md CHANGED
@@ -26,7 +26,6 @@ tags:
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  - mteb
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  language: en
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  inference: false
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- license: apache-2.0
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  model-index:
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  - name: INSTRUCTOR
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  results:
@@ -1900,7 +1899,7 @@ model-index:
1900
  - type: map_at_5
1901
  value: 9.149000000000001
1902
  - type: mrr_at_1
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- value: 21.0
1904
  - type: mrr_at_10
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  value: 31.416
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  - type: mrr_at_100
@@ -1912,7 +1911,7 @@ model-index:
1912
  - type: mrr_at_5
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  value: 29.976999999999997
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  - type: ndcg_at_1
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- value: 21.0
1916
  - type: ndcg_at_10
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  value: 18.551000000000002
1918
  - type: ndcg_at_100
@@ -1924,7 +1923,7 @@ model-index:
1924
  - type: ndcg_at_5
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  value: 15.204999999999998
1926
  - type: precision_at_1
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- value: 21.0
1928
  - type: precision_at_10
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  value: 9.84
1930
  - type: precision_at_100
@@ -2081,7 +2080,7 @@ model-index:
2081
  - type: map_at_5
2082
  value: 58.272999999999996
2083
  - type: mrr_at_1
2084
- value: 53.0
2085
  - type: mrr_at_10
2086
  value: 61.102000000000004
2087
  - type: mrr_at_100
@@ -2093,7 +2092,7 @@ model-index:
2093
  - type: mrr_at_5
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  value: 60.128
2095
  - type: ndcg_at_1
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- value: 53.0
2097
  - type: ndcg_at_10
2098
  value: 64.43100000000001
2099
  - type: ndcg_at_100
@@ -2105,7 +2104,7 @@ model-index:
2105
  - type: ndcg_at_5
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  value: 61.888
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  - type: precision_at_1
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- value: 53.0
2109
  - type: precision_at_10
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  value: 8.767
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  - type: precision_at_100
@@ -2257,7 +2256,7 @@ model-index:
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  - type: map_at_5
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  value: 0.8019999999999999
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  - type: mrr_at_1
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- value: 72.0
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  - type: mrr_at_10
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  value: 83.39999999999999
2263
  - type: mrr_at_100
@@ -2269,7 +2268,7 @@ model-index:
2269
  - type: mrr_at_5
2270
  value: 83.06700000000001
2271
  - type: ndcg_at_1
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- value: 66.0
2273
  - type: ndcg_at_10
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  value: 58.059000000000005
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  - type: ndcg_at_100
@@ -2281,7 +2280,7 @@ model-index:
2281
  - type: ndcg_at_5
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  value: 63.005
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  - type: precision_at_1
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- value: 72.0
2285
  - type: precision_at_10
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  value: 61.4
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  - type: precision_at_100
@@ -2289,7 +2288,7 @@ model-index:
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  - type: precision_at_1000
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  value: 19.866
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  - type: precision_at_3
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- value: 70.0
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  - type: precision_at_5
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  value: 68.8
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  - type: recall_at_1
@@ -2607,4 +2606,4 @@ clustering_model = sklearn.cluster.MiniBatchKMeans(n_clusters=2)
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  clustering_model.fit(embeddings)
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  cluster_assignment = clustering_model.labels_
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  print(cluster_assignment)
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- ```
 
26
  - mteb
27
  language: en
28
  inference: false
 
29
  model-index:
30
  - name: INSTRUCTOR
31
  results:
 
1899
  - type: map_at_5
1900
  value: 9.149000000000001
1901
  - type: mrr_at_1
1902
+ value: 21
1903
  - type: mrr_at_10
1904
  value: 31.416
1905
  - type: mrr_at_100
 
1911
  - type: mrr_at_5
1912
  value: 29.976999999999997
1913
  - type: ndcg_at_1
1914
+ value: 21
1915
  - type: ndcg_at_10
1916
  value: 18.551000000000002
1917
  - type: ndcg_at_100
 
1923
  - type: ndcg_at_5
1924
  value: 15.204999999999998
1925
  - type: precision_at_1
1926
+ value: 21
1927
  - type: precision_at_10
1928
  value: 9.84
1929
  - type: precision_at_100
 
2080
  - type: map_at_5
2081
  value: 58.272999999999996
2082
  - type: mrr_at_1
2083
+ value: 53
2084
  - type: mrr_at_10
2085
  value: 61.102000000000004
2086
  - type: mrr_at_100
 
2092
  - type: mrr_at_5
2093
  value: 60.128
2094
  - type: ndcg_at_1
2095
+ value: 53
2096
  - type: ndcg_at_10
2097
  value: 64.43100000000001
2098
  - type: ndcg_at_100
 
2104
  - type: ndcg_at_5
2105
  value: 61.888
2106
  - type: precision_at_1
2107
+ value: 53
2108
  - type: precision_at_10
2109
  value: 8.767
2110
  - type: precision_at_100
 
2256
  - type: map_at_5
2257
  value: 0.8019999999999999
2258
  - type: mrr_at_1
2259
+ value: 72
2260
  - type: mrr_at_10
2261
  value: 83.39999999999999
2262
  - type: mrr_at_100
 
2268
  - type: mrr_at_5
2269
  value: 83.06700000000001
2270
  - type: ndcg_at_1
2271
+ value: 66
2272
  - type: ndcg_at_10
2273
  value: 58.059000000000005
2274
  - type: ndcg_at_100
 
2280
  - type: ndcg_at_5
2281
  value: 63.005
2282
  - type: precision_at_1
2283
+ value: 72
2284
  - type: precision_at_10
2285
  value: 61.4
2286
  - type: precision_at_100
 
2288
  - type: precision_at_1000
2289
  value: 19.866
2290
  - type: precision_at_3
2291
+ value: 70
2292
  - type: precision_at_5
2293
  value: 68.8
2294
  - type: recall_at_1
 
2606
  clustering_model.fit(embeddings)
2607
  cluster_assignment = clustering_model.labels_
2608
  print(cluster_assignment)
2609
+ ```