diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -8,20 +8,20 @@ tags: metrics: - accuracy widget: -- text: The pre-study survey questionnaire was designed to measure the participants' - knowledge about the controversial topic. -- text: To test these hypotheses, we conducted a series of experiments in which we - modified NGE to eliminate one or more of these suspected problems and measured - the resulting change in performance. -- text: After this factor has been controlled for, the results suggest that there - is a complex relationship between the characteristics of the children born during - the first marriage and the likelihood of having a child after separation. -- text: It is apparent that the predicted pressure trace for the advanced injection - case (Fig. -- text: Evidence for linkage and association of obesity-related quantitative traits - to chromosome 1q43 has been reported in the Quebec Family Study (QFS) and in populations - of Caribbean Hispanic ancestries yet no specific candidate locus has been replicated - to date. +- text: In these circumstances, only clearly identifiable recidivism rates were included + in the study. +- text: Semi-automatic tools have been developed to aid in the processing of these + representations. +- text: The purpose of this paper is to estimate the Certain Coefficient for generalized + Starlike functions with reference to symmetric points described on the open unit + disk for which R k λ ,δ (φ ) of normalized analytic functions f (z) that lies + in a region with reference to 1 and symmetric with reference to the real axis. +- text: The other two SNPs were selected on the basis of the linkage disequilibrium + (LD) structure of the gene, allele frequency, and available Haplotype Map data + (http://hapmap. +- text: It might be possible to formulate a general condition in this sense similar + to the condition on the Runge-Kutta methods but at present we do not know whether + such a condition actually exists. pipeline_tag: text-classification inference: true base_model: jinaai/jina-embeddings-v2-base-en @@ -37,7 +37,7 @@ model-index: split: test metrics: - type: accuracy - value: 0.9565217391304348 + value: 0.9629629629629629 name: Accuracy --- @@ -57,7 +57,7 @@ The model has been trained using an efficient few-shot learning technique that i - **Sentence Transformer body:** [jinaai/jina-embeddings-v2-base-en](https://huggingface.co/jinaai/jina-embeddings-v2-base-en) - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - **Maximum Sequence Length:** 8192 tokens -- **Number of Classes:** 77 classes +- **Number of Classes:** 9 classes @@ -71,90 +71,22 @@ The model has been trained using an efficient few-shot learning technique that i ### Model Labels | Label | Examples | |:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| 1 | | -| 2 | | -| 3 | | -| 4 | | -| 5 | | -| 6 | | -| 7 | | -| 8 | | -| 9 | | -| 10 | | -| 11 | | -| 12 | | -| 13 | | -| 14 | | -| 16 | | -| 17 | | -| 18 | | -| 19 | | -| 20 | | -| 21 | | -| 22 | | -| 23 | | -| 24 | | -| 25 | | -| 26 | | -| 27 | | -| 28 | | -| 30 | | -| 31 | | -| 32 | | -| 33 | | -| 34 | | -| 35 | | -| 36 | | -| 37 | | -| 38 | | -| 40 | | -| 41 | | -| 42 | | -| 43 | | -| 44 | | -| 45 | | -| 46 | | -| 47 | | -| 48 | | -| 49 | | -| 50 | | -| 51 | | -| 52 | | -| 53 | | -| 54 | | -| 55 | | -| 56 | | -| 57 | | -| 58 | | -| 59 | | -| 60 | | -| 61 | | -| 62 | | -| 63 | | -| 64 | | -| 65 | | -| 66 | | -| 67 | | -| 68 | | -| 69 | | -| 70 | | -| 71 | | -| 72 | | -| 73 | | -| 74 | | -| 75 | | -| 76 | | -| 77 | | -| 78 | | -| 79 | | -| 80 | | +| 1 | | +| 2 | | +| 3 | | +| 4 | | +| 5 | | +| 6 | | +| 7 | | +| 8 | | +| 9 | | ## Evaluation ### Metrics | Label | Accuracy | |:--------|:---------| -| **all** | 0.9565 | +| **all** | 0.9630 | ## Uses @@ -174,7 +106,7 @@ from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("Corran/Jina_Sci") # Run inference -preds = model("It is apparent that the predicted pressure trace for the advanced injection case (Fig.") +preds = model("Semi-automatic tools have been developed to aid in the processing of these representations.") ```