license: apache-2.0
Here we estimate the performance of the CLIP embeddings (contrastive training between text - image data).
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Evaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported57.493
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported23.594
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported52.202
- accuracy on MTEB AmazonReviewsClassification (en)test set self-reported30.590
- f1 on MTEB AmazonReviewsClassification (en)test set self-reported30.418
- accuracy on MTEB Banking77Classificationtest set self-reported73.419
- f1 on MTEB Banking77Classificationtest set self-reported73.365
- v_measure on MTEB BiorxivClusteringP2Ptest set self-reported29.331
- v_measure on MTEB BiorxivClusteringS2Stest set self-reported27.812
- accuracy on MTEB EmotionClassificationtest set self-reported33.620
- f1 on MTEB EmotionClassificationtest set self-reported29.639
- accuracy on MTEB ImdbClassificationtest set self-reported56.172
- ap on MTEB ImdbClassificationtest set self-reported53.589
- f1 on MTEB ImdbClassificationtest set self-reported55.864
- accuracy on MTEB MTOPDomainClassification (en)test set self-reported87.073
- f1 on MTEB MTOPDomainClassification (en)test set self-reported86.637
- accuracy on MTEB MTOPIntentClassification (en)test set self-reported61.956
- f1 on MTEB MTOPIntentClassification (en)test set self-reported41.662
- accuracy on MTEB MassiveIntentClassification (en)test set self-reported62.962
- f1 on MTEB MassiveIntentClassification (en)test set self-reported60.204