Update README.md

README.md

@@ -1,54 +1,54 @@
 ---
 license: bigscience-bloom-rail-1.0
 language:
-  - ak
-  - ar
-  - as
-  - bm
-  - bn
-  - ca
-  - code
-  - en
-  - es
-  - eu
-  - fon
-  - fr
-  - gu
-  - hi
-  - id
-  - ig
-  - ki
-  - kn
-  - lg
-  - ln
-  - ml
-  - mr
-  - ne
-  - nso
-  - ny
-  - or
-  - pa
-  - pt
-  - rn
-  - rw
-  - sn
-  - st
-  - sw
-  - ta
-  - te
-  - tn
-  - ts
-  - tum
-  - tw
-  - ur
-  - vi
-  - wo
-  - xh
-  - yo
-  - zh
-  - zhs
-  - zht
-  - zu
+- ak
+- ar
+- as
+- bm
+- bn
+- ca
+- code
+- en
+- es
+- eu
+- fon
+- fr
+- gu
+- hi
+- id
+- ig
+- ki
+- kn
+- lg
+- ln
+- ml
+- mr
+- ne
+- nso
+- ny
+- or
+- pa
+- pt
+- rn
+- rw
+- sn
+- st
+- sw
+- ta
+- te
+- tn
+- ts
+- tum
+- tw
+- ur
+- vi
+- wo
+- xh
+- yo
+- zh
+- zhs
+- zht
+- zu
 tags:
 - mteb
 model-index:
@@ -2342,7 +2342,7 @@ model-index:
     - type: recall_at_1000
       value: 84.3
     - type: recall_at_3
-      value: 49.0
+      value: 49
     - type: recall_at_5
       value: 50.4
   - task:
@@ -2690,7 +2690,7 @@ model-index:
     - type: mrr_at_5
       value: 86.914
     - type: ndcg_at_1
-      value: 81.0
+      value: 81
     - type: ndcg_at_10
       value: 88.009
     - type: ndcg_at_100
@@ -2702,7 +2702,7 @@ model-index:
     - type: ndcg_at_5
       value: 86.75399999999999
     - type: precision_at_1
-      value: 81.0
+      value: 81
     - type: precision_at_10
       value: 13.343
     - type: precision_at_100
@@ -3332,19 +3332,19 @@ model-index:
     - type: map_at_5
       value: 1.169
     - type: mrr_at_1
-      value: 94.0
+      value: 94
     - type: mrr_at_10
-      value: 97.0
+      value: 97
     - type: mrr_at_100
-      value: 97.0
+      value: 97
     - type: mrr_at_1000
-      value: 97.0
+      value: 97
     - type: mrr_at_3
-      value: 97.0
+      value: 97
     - type: mrr_at_5
-      value: 97.0
+      value: 97
     - type: ndcg_at_1
-      value: 88.0
+      value: 88
     - type: ndcg_at_10
       value: 83.21
     - type: ndcg_at_100
@@ -3356,7 +3356,7 @@ model-index:
     - type: ndcg_at_5
       value: 86.20100000000001
     - type: precision_at_1
-      value: 94.0
+      value: 94
     - type: precision_at_10
       value: 88.2
     - type: precision_at_100
@@ -3474,13 +3474,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 42.0
+      value: 42
     - type: f1
       value: 36.81003102453103
     - type: precision
       value: 35.19870269535562
     - type: recall
-      value: 42.0
+      value: 42
   - task:
       type: BitextMining
     dataset:
@@ -3559,13 +3559,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 9.0
+      value: 9
     - type: f1
       value: 6.926590762281661
     - type: precision
       value: 6.507185696775364
     - type: recall
-      value: 9.0
+      value: 9
   - task:
       type: BitextMining
     dataset:
@@ -3712,13 +3712,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 16.0
+      value: 16
     - type: f1
       value: 12.172850459161385
     - type: precision
       value: 11.27855570316309
     - type: recall
-      value: 16.0
+      value: 16
   - task:
       type: BitextMining
     dataset:
@@ -3763,13 +3763,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 21.0
+      value: 21
     - type: f1
       value: 17.006564035803166
     - type: precision
       value: 15.844832112332114
     - type: recall
-      value: 21.0
+      value: 21
   - task:
       type: BitextMining
     dataset:
@@ -3814,13 +3814,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 69.0
+      value: 69
     - type: f1
       value: 63.68992285492286
     - type: precision
       value: 61.72837301587302
     - type: recall
-      value: 69.0
+      value: 69
   - task:
       type: BitextMining
     dataset:
@@ -3865,13 +3865,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 69.0
+      value: 69
     - type: f1
       value: 62.61056277056276
     - type: precision
       value: 59.96357142857143
     - type: recall
-      value: 69.0
+      value: 69
   - task:
       type: BitextMining
     dataset:
@@ -4188,13 +4188,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 9.0
+      value: 9
     - type: f1
       value: 6.952605595133894
     - type: precision
       value: 6.457724621713984
     - type: recall
-      value: 9.0
+      value: 9
   - task:
       type: BitextMining
     dataset:
@@ -4341,13 +4341,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 95.0
+      value: 95
     - type: f1
       value: 93.61666666666666
     - type: precision
       value: 92.93333333333332
     - type: recall
-      value: 95.0
+      value: 95
   - task:
       type: BitextMining
     dataset:
@@ -4443,13 +4443,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 97.0
+      value: 97
     - type: f1
       value: 96.05
     - type: precision
       value: 95.58333333333334
     - type: recall
-      value: 97.0
+      value: 97
   - task:
       type: BitextMining
     dataset:
@@ -4851,13 +4851,13 @@ model-index:
       revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
     metrics:
     - type: accuracy
-      value: 78.0
+      value: 78
     - type: f1
       value: 73.95134920634919
     - type: precision
       value: 72.3770634920635
     - type: recall
-      value: 78.0
+      value: 78
   - task:
       type: BitextMining
     dataset:
@@ -5607,6 +5607,7 @@ model-index:
       value: 65.23766736490957
     - type: f1
       value: 82.17794239849368
+library_name: sentence-transformers
 ---
 
 # Model Card for udever-bloom
@@ -5800,4 +5801,4 @@ Negatives for SNLI and MultiNLI are randomly sampled.
   journal={arXiv preprint arXiv:2310.08232},
   year={2023}
 }
-```
+```