diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -9,6 +9,8884 @@ tags: - embeddings - static-embeddings - sentence-transformers +- mteb +--- +model-index: +- name: red-beetle-base-v1.1 + results: + - dataset: + config: en-ext + name: MTEB AmazonCounterfactualClassification (en-ext) + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + split: test + type: mteb/amazon_counterfactual + metrics: + - type: accuracy + value: 68.51574212893554 + - type: ap + value: 18.26482128271432 + - type: ap_weighted + value: 18.26482128271432 + - type: f1 + value: 56.018664848414076 + - type: f1_weighted + value: 74.48440726200506 + - type: main_score + value: 68.51574212893554 + task: + type: Classification + - dataset: + config: en + name: MTEB AmazonCounterfactualClassification (en) + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + split: test + type: mteb/amazon_counterfactual + metrics: + - type: accuracy + value: 70.3731343283582 + - type: ap + value: 32.733191285536655 + - 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type: main_score + value: 51.185625353706854 + task: + type: Classification + - dataset: + config: default + name: MTEB TwentyNewsgroupsClustering (default) + revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 + split: test + type: mteb/twentynewsgroups-clustering + metrics: + - type: main_score + value: 25.21775024668781 + - type: v_measure + value: 25.21775024668781 + - type: v_measure_std + value: 1.351620001506375 + task: + type: Clustering + - dataset: + config: default + name: MTEB TwitterSemEval2015 (default) + revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 + split: test + type: mteb/twittersemeval2015-pairclassification + metrics: + - type: cosine_accuracy + value: 81.92763902962389 + - type: cosine_accuracy_threshold + value: 71.09723687171936 + - type: cosine_ap + value: 57.964594703670656 + - type: cosine_f1 + value: 55.27800161160354 + - type: cosine_f1_threshold + value: 62.15030550956726 + - type: cosine_precision + value: 49.030018378599145 + - type: cosine_recall + value: 63.35092348284961 + - type: dot_accuracy + value: 78.24402455742981 + - type: dot_accuracy_threshold + value: 68270.95336914062 + - type: dot_ap + value: 43.171963102490615 + - type: dot_f1 + value: 47.39143106965899 + - type: dot_f1_threshold + value: 33946.66748046875 + - type: dot_precision + value: 37.505766569275714 + - type: dot_recall + value: 64.35356200527704 + - type: euclidean_accuracy + value: 79.22155331704118 + - type: euclidean_accuracy_threshold + value: 1523.3871459960938 + - type: euclidean_ap + value: 46.52726303607135 + - type: euclidean_f1 + value: 46.406523005241695 + - type: euclidean_f1_threshold + value: 2067.5140380859375 + - type: euclidean_precision + value: 41.54327424400417 + - type: euclidean_recall + value: 52.55936675461741 + - type: main_score + value: 57.9645989101073 + - type: manhattan_accuracy + value: 79.41825117720688 + - type: manhattan_accuracy_threshold + value: 28691.644287109375 + - type: manhattan_ap + value: 47.06475509042154 + - type: manhattan_f1 + value: 46.79797145889845 + - type: manhattan_f1_threshold + value: 39006.52160644531 + - type: manhattan_precision + value: 42.31179355939433 + - type: manhattan_recall + value: 52.34828496042216 + - type: max_accuracy + value: 81.92763902962389 + - type: max_ap + value: 57.9645989101073 + - type: max_f1 + value: 55.27800161160354 + - type: max_precision + value: 49.030018378599145 + - type: max_recall + value: 64.35356200527704 + - type: similarity_accuracy + value: 81.92763902962389 + - type: similarity_accuracy_threshold + value: 71.09723091125488 + - type: similarity_ap + value: 57.9645989101073 + - type: similarity_f1 + value: 55.27800161160354 + - type: similarity_f1_threshold + value: 62.15031147003174 + - type: similarity_precision + value: 49.030018378599145 + - type: similarity_recall + value: 63.35092348284961 + task: + type: PairClassification + - dataset: + config: default + name: MTEB TwitterURLCorpus (default) + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + split: test + type: mteb/twitterurlcorpus-pairclassification + metrics: + - type: cosine_accuracy + value: 86.96588659913843 + - type: cosine_accuracy_threshold + value: 61.520421504974365 + - type: cosine_ap + value: 81.7361816102444 + - type: cosine_f1 + value: 73.97320448056227 + - type: cosine_f1_threshold + value: 55.81372380256653 + - type: cosine_precision + value: 70.50942079553386 + - type: cosine_recall + value: 77.79488758854328 + - type: dot_accuracy + value: 82.9413591027283 + - type: dot_accuracy_threshold + value: 22375.634765625 + - type: dot_ap + value: 70.36676649129193 + - type: dot_f1 + value: 67.16835375599362 + - type: dot_f1_threshold + value: 16350.4638671875 + - type: dot_precision + value: 59.176249706641634 + - type: dot_recall + value: 77.65629812134279 + - type: euclidean_accuracy + value: 82.51251600884852 + - type: euclidean_accuracy_threshold + value: 1394.6439743041992 + - type: euclidean_ap + value: 68.29382960739675 + - type: euclidean_f1 + value: 60.384865526607754 + - type: euclidean_f1_threshold + value: 1643.9237594604492 + - type: euclidean_precision + value: 60.01064557828302 + - type: euclidean_recall + value: 60.763781952571605 + - type: main_score + value: 81.73619060168708 + - type: manhattan_accuracy + value: 82.74149105444948 + - type: manhattan_accuracy_threshold + value: 27013.568115234375 + - type: manhattan_ap + value: 68.65648959722192 + - type: manhattan_f1 + value: 60.770683792973166 + - type: manhattan_f1_threshold + value: 31251.20849609375 + - type: manhattan_precision + value: 59.65732087227414 + - type: manhattan_recall + value: 61.926393594086846 + - type: max_accuracy + value: 86.96588659913843 + - type: max_ap + value: 81.73619060168708 + - type: max_f1 + value: 73.97320448056227 + - type: max_precision + value: 70.50942079553386 + - type: max_recall + value: 77.79488758854328 + - type: similarity_accuracy + value: 86.96588659913843 + - type: similarity_accuracy_threshold + value: 61.520421504974365 + - type: similarity_ap + value: 81.73619060168708 + - type: similarity_f1 + value: 73.97320448056227 + - type: similarity_f1_threshold + value: 55.81372380256653 + - type: similarity_precision + value: 70.50942079553386 + - type: similarity_recall + value: 77.79488758854328 + task: + type: PairClassification + --- # 🪲 red-beetle-base-v1.1 Model Card