diff --git "a/README.md" "b/README.md"
--- "a/README.md"
+++ "b/README.md"
@@ -84,6 +84,8965 @@ language:
- vi
- yo
- zh
+model-index:
+- name: snowflake-arctic-embed-m-v2.0
+ results:
+ - dataset:
+ config: en-ext
+ name: MTEB AmazonCounterfactualClassification (en-ext)
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+ split: test
+ type: mteb/amazon_counterfactual
+ metrics:
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+ value: 73.07430000000001
+ - type: ap
+ value: 18.077399999999997
+ - type: ap_weighted
+ value: 18.077399999999997
+ - type: main_score
+ value: 66.6867
+ task:
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+ - dataset:
+ config: en
+ name: MTEB AmazonCounterfactualClassification (en)
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+ split: test
+ type: mteb/amazon_counterfactual
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+ - type: ap
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+ - type: ap_weighted
+ value: 30.279099999999996
+ - type: main_score
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+ task:
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+ - dataset:
+ config: default
+ name: MTEB AmazonPolarityClassification (default)
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+ split: test
+ type: mteb/amazon_polarity
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+ task:
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+ name: MTEB AmazonReviewsClassification (en)
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ split: test
+ type: mteb/amazon_reviews_multi
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+ name: MTEB AskUbuntuDupQuestions (default)
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+ name: MTEB STS17 (en-en)
+ revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+ split: test
+ type: mteb/sts17-crosslingual-sts
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+ - type: cosine_pearson
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+ - type: manhattan_spearman
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+ - type: euclidean_pearson
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+ - type: main_score
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+ name: MTEB STS17 (en-tr)
+ revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+ split: test
+ type: mteb/sts17-crosslingual-sts
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+ name: MTEB STS17 (it-en)
+ revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+ split: test
+ type: mteb/sts17-crosslingual-sts
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+ name: MTEB STS17 (nl-en)
+ revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+ split: test
+ type: mteb/sts17-crosslingual-sts
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+ - type: spearman
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+ - type: cosine_spearman
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+ name: MTEB STS17 (en-ar)
+ revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+ split: test
+ type: mteb/sts17-crosslingual-sts
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+ - type: main_score
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+ name: MTEB STS17 (en-de)
+ revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+ split: test
+ type: mteb/sts17-crosslingual-sts
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+ name: MTEB STS22 (zh-en)
+ revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+ split: test
+ type: mteb/sts22-crosslingual-sts
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+ - type: main_score
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+ name: MTEB STS22 (es-en)
+ revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+ split: test
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+ name: MTEB STS22 (de-en)
+ revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
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+ name: MTEB STS22 (pl-en)
+ revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
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+ revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+ split: test
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+ name: MTEB STSBenchmark (default)
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+ split: test
+ type: mteb/stsbenchmark-sts
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+ name: MTEB SciDocsRR (default)
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+ split: test
+ type: mteb/scidocs-reranking
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+ name: MTEB SciFact (default)
+ revision: 0228b52cf27578f30900b9e5271d331663a030d7
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+ name: MTEB SprintDuplicateQuestions (default)
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+ split: test
+ type: mteb/sprintduplicatequestions-pairclassification
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+ - type: main_score
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+ - dataset:
+ config: default
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+ type: mteb/toxic_conversations_50k
+ metrics:
+ - type: accuracy
+ value: 64.8096
+ - type: f1
+ value: 49.844300000000004
+ - type: f1_weighted
+ value: 72.5251
+ - type: ap
+ value: 11.7519
+ - type: ap_weighted
+ value: 11.7519
+ - type: main_score
+ value: 64.8096
+ task:
+ type: Classification
+ - dataset:
+ config: default
+ name: MTEB TweetSentimentExtractionClassification (default)
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+ split: test
+ type: mteb/tweet_sentiment_extraction
+ metrics:
+ - type: accuracy
+ value: 58.1692
+ - type: f1
+ value: 58.4408
+ - type: f1_weighted
+ value: 57.565599999999996
+ - type: main_score
+ value: 58.1692
+ task:
+ type: Classification
+ - dataset:
+ config: default
+ name: MTEB TwentyNewsgroupsClustering (default)
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+ split: test
+ type: mteb/twentynewsgroups-clustering
+ metrics:
+ - type: v_measure
+ value: 39.293
+ - type: v_measure_std
+ value: 1.5684
+ - type: main_score
+ value: 39.293
+ task:
+ type: Clustering
+ - dataset:
+ config: default
+ name: MTEB TwitterSemEval2015 (default)
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+ split: test
+ type: mteb/twittersemeval2015-pairclassification
+ metrics:
+ - type: similarity_accuracy
+ value: 83.29260000000001
+ - type: similarity_accuracy_threshold
+ value: 78.2732
+ - type: similarity_f1
+ value: 60.656600000000005
+ - type: similarity_f1_threshold
+ value: 73.4961
+ - type: similarity_precision
+ value: 59.007
+ - type: similarity_recall
+ value: 62.4011
+ - type: similarity_ap
+ value: 64.7501
+ - type: cosine_accuracy
+ value: 83.29260000000001
+ - type: cosine_accuracy_threshold
+ value: 78.2732
+ - type: cosine_f1
+ value: 60.656600000000005
+ - type: cosine_f1_threshold
+ value: 73.4961
+ - type: cosine_precision
+ value: 59.007
+ - type: cosine_recall
+ value: 62.4011
+ - type: cosine_ap
+ value: 64.7501
+ - type: manhattan_accuracy
+ value: 83.2986
+ - type: manhattan_accuracy_threshold
+ value: 1476.7148
+ - type: manhattan_f1
+ value: 60.7459
+ - type: manhattan_f1_threshold
+ value: 1607.9180000000001
+ - type: manhattan_precision
+ value: 59.0581
+ - type: manhattan_recall
+ value: 62.53300000000001
+ - type: manhattan_ap
+ value: 64.76859999999999
+ - type: euclidean_accuracy
+ value: 83.29260000000001
+ - type: euclidean_accuracy_threshold
+ value: 65.9194
+ - type: euclidean_f1
+ value: 60.656600000000005
+ - type: euclidean_f1_threshold
+ value: 72.8065
+ - type: euclidean_precision
+ value: 59.007
+ - type: euclidean_recall
+ value: 62.4011
+ - type: euclidean_ap
+ value: 64.7501
+ - type: dot_accuracy
+ value: 83.29260000000001
+ - type: dot_accuracy_threshold
+ value: 78.2731
+ - type: dot_f1
+ value: 60.656600000000005
+ - type: dot_f1_threshold
+ value: 73.4961
+ - type: dot_precision
+ value: 59.007
+ - type: dot_recall
+ value: 62.4011
+ - type: dot_ap
+ value: 64.7501
+ - type: max_accuracy
+ value: 83.2986
+ - type: max_f1
+ value: 60.7459
+ - type: max_precision
+ value: 59.0581
+ - type: max_recall
+ value: 62.53300000000001
+ - type: max_ap
+ value: 64.76859999999999
+ - type: main_score
+ value: 64.76859999999999
+ task:
+ type: PairClassification
+ - dataset:
+ config: default
+ name: MTEB TwitterURLCorpus (default)
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+ split: test
+ type: mteb/twitterurlcorpus-pairclassification
+ metrics:
+ - type: similarity_accuracy
+ value: 89.0247
+ - type: similarity_accuracy_threshold
+ value: 69.271
+ - type: similarity_f1
+ value: 78.24419999999999
+ - type: similarity_f1_threshold
+ value: 66.2183
+ - type: similarity_precision
+ value: 76.616
+ - type: similarity_recall
+ value: 79.943
+ - type: similarity_ap
+ value: 85.9494
+ - type: cosine_accuracy
+ value: 89.0247
+ - type: cosine_accuracy_threshold
+ value: 69.271
+ - type: cosine_f1
+ value: 78.24419999999999
+ - type: cosine_f1_threshold
+ value: 66.2183
+ - type: cosine_precision
+ value: 76.616
+ - type: cosine_recall
+ value: 79.943
+ - type: cosine_ap
+ value: 85.9494
+ - type: manhattan_accuracy
+ value: 89.0267
+ - type: manhattan_accuracy_threshold
+ value: 1750.3544000000002
+ - type: manhattan_f1
+ value: 78.2188
+ - type: manhattan_f1_threshold
+ value: 1837.7304
+ - type: manhattan_precision
+ value: 75.1472
+ - type: manhattan_recall
+ value: 81.5522
+ - type: manhattan_ap
+ value: 85.9496
+ - type: euclidean_accuracy
+ value: 89.0247
+ - type: euclidean_accuracy_threshold
+ value: 78.3951
+ - type: euclidean_f1
+ value: 78.24419999999999
+ - type: euclidean_f1_threshold
+ value: 82.197
+ - type: euclidean_precision
+ value: 76.616
+ - type: euclidean_recall
+ value: 79.943
+ - type: euclidean_ap
+ value: 85.9494
+ - type: dot_accuracy
+ value: 89.0247
+ - type: dot_accuracy_threshold
+ value: 69.271
+ - type: dot_f1
+ value: 78.24419999999999
+ - type: dot_f1_threshold
+ value: 66.2183
+ - type: dot_precision
+ value: 76.616
+ - type: dot_recall
+ value: 79.943
+ - type: dot_ap
+ value: 85.9494
+ - type: max_accuracy
+ value: 89.0267
+ - type: max_f1
+ value: 78.24419999999999
+ - type: max_precision
+ value: 76.616
+ - type: max_recall
+ value: 81.5522
+ - type: max_ap
+ value: 85.9496
+ - type: main_score
+ value: 85.9496
+ task:
+ type: PairClassification
---
Snowflake's Arctic-embed-m-v2.0