diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -1,3 +1,8988 @@ +--- +library_name: peft +license: mit +language: +- en +pipeline_tag: sentence-similarity +tags: +- text-embedding +- embeddings +- information-retrieval +- beir +- text-classification +- language-model +- text-clustering +- text-semantic-similarity +- text-evaluation +- text-reranking +- feature-extraction +- sentence-similarity +- Sentence Similarity +- natural_questions +- ms_marco +- fever +- hotpot_qa +- mteb +model-index: +- name: BinGSE-Meta-Llama-3-8B-Instruct + results: + - dataset: + config: en-ext + name: MTEB AmazonCounterfactualClassification (en-ext) + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + split: test + type: mteb/amazon_counterfactual + metrics: + - type: accuracy + value: 80.7271364317841 + - type: ap + value: 29.57781615779065 + - type: ap_weighted + value: 29.57781615779065 + - type: f1 + value: 67.88722644497633 + - type: f1_weighted + value: 83.93210384487763 + - 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dataset: + config: default + name: MTEB TweetSentimentExtractionClassification (default) + revision: d604517c81ca91fe16a244d1248fc021f9ecee7a + split: test + type: mteb/tweet_sentiment_extraction + metrics: + - type: accuracy + value: 64.03225806451613 + - type: f1 + value: 64.06843534121843 + - type: f1_weighted + value: 62.74796899202356 + - type: main_score + value: 64.03225806451613 + task: + type: Classification + - dataset: + config: default + name: MTEB TwentyNewsgroupsClustering (default) + revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 + split: test + type: mteb/twentynewsgroups-clustering + metrics: + - type: main_score + value: 53.5182998227727 + - type: v_measure + value: 53.5182998227727 + - type: v_measure_std + value: 1.8758215247032688 + task: + type: Clustering + - dataset: + config: default + name: MTEB TwitterSemEval2015 (default) + revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 + split: test + type: mteb/twittersemeval2015-pairclassification + metrics: + - type: cosine_accuracy + value: 88.77630088812064 + - 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type: euclidean_recall + value: 79.15567282321899 + - type: main_score + value: 82.39103516928604 + - type: manhattan_accuracy + value: 88.72265601716636 + - type: manhattan_accuracy_threshold + value: 3392.3141479492188 + - type: manhattan_ap + value: 82.37303670339044 + - type: manhattan_f1 + value: 74.91452450297581 + - type: manhattan_f1_threshold + value: 3631.7977905273438 + - type: manhattan_precision + value: 72.02337472607742 + - type: manhattan_recall + value: 78.04749340369393 + - type: max_accuracy + value: 88.77630088812064 + - type: max_ap + value: 82.39103516928604 + - type: max_f1 + value: 74.91452450297581 + - type: max_precision + value: 72.02337472607742 + - type: max_recall + value: 79.15567282321899 + - type: similarity_accuracy + value: 88.77630088812064 + - type: similarity_accuracy_threshold + value: 1776.1724472045898 + - type: similarity_ap + value: 82.39103516928604 + - type: similarity_f1 + value: 74.85029940119759 + - type: similarity_f1_threshold + value: 1682.8865051269531 + - type: similarity_precision + value: 70.9891150023663 + - type: similarity_recall + value: 79.15567282321899 + task: + type: PairClassification + - dataset: + config: default + name: MTEB TwitterURLCorpus (default) + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + split: test + type: mteb/twitterurlcorpus-pairclassification + metrics: + - type: cosine_accuracy + value: 89.86688399891334 + - type: cosine_accuracy_threshold + value: 72.39344120025635 + - type: cosine_ap + value: 87.60291936910795 + - type: cosine_f1 + value: 80.1902671057446 + - type: cosine_f1_threshold + value: 69.8064923286438 + - type: cosine_precision + value: 76.40496444010599 + - type: cosine_recall + value: 84.3701878657222 + - type: dot_accuracy + value: 89.86688399891334 + - type: dot_accuracy_threshold + value: 72.39343523979187 + - type: dot_ap + value: 87.60292256175723 + - type: dot_f1 + value: 80.1902671057446 + - type: dot_f1_threshold + value: 69.80648040771484 + - type: dot_precision + value: 76.40496444010599 + - type: dot_recall + value: 84.3701878657222 + - type: euclidean_accuracy + value: 89.86688399891334 + - type: euclidean_accuracy_threshold + value: 74.30553436279297 + - type: euclidean_ap + value: 87.60291559616975 + - type: euclidean_f1 + value: 80.1902671057446 + - type: euclidean_f1_threshold + value: 77.70909070968628 + - type: euclidean_precision + value: 76.40496444010599 + - type: euclidean_recall + value: 84.3701878657222 + - type: main_score + value: 87.60538403560003 + - type: manhattan_accuracy + value: 89.88822913028291 + - type: manhattan_accuracy_threshold + value: 3783.2366943359375 + - type: manhattan_ap + value: 87.60538403560003 + - type: manhattan_f1 + value: 80.16710642040458 + - type: manhattan_f1_threshold + value: 3948.430633544922 + - type: manhattan_precision + value: 76.4895104895105 + - type: manhattan_recall + value: 84.21619956883278 + - type: max_accuracy + value: 89.88822913028291 + - type: max_ap + value: 87.60538403560003 + - type: max_f1 + value: 80.1902671057446 + - type: max_precision + value: 76.4895104895105 + - type: max_recall + value: 84.3701878657222 + - type: similarity_accuracy + value: 89.86688399891334 + - type: similarity_accuracy_threshold + value: 1643.6103820800781 + - type: similarity_ap + value: 87.6029128769812 + - type: similarity_f1 + value: 80.1902671057446 + - type: similarity_f1_threshold + value: 1584.8767280578613 + - type: similarity_precision + value: 76.40496444010599 + - type: similarity_recall + value: 84.3701878657222 + task: + type: PairClassification +---