Model: HelgeKn/SemEval-multi-class-20
Author: HelgeKn
Pipeline: text-classification
Library: setfit
Tags: setfit, safetensors, mpnet, sentence-transformers, text-classification, generated_from_setfit_trainer, arxiv:2209.11055, base_model:sentence-transformers/paraphrase-mpnet-base-v2, base_model:finetune:sentence-transformers/paraphrase-mpnet-base-v2, model-index, region:us
Base models (finetune): id: sentence-transformers/paraphrase-mpnet-base-v2
Card metadata: library_name: setfit
tags: setfit, sentence-transformers, text-classification, generated_from_setfit_trainer
metrics: accuracy
widget: But their arguments about the effect of the intense coverage of the trial may draw the most interest . , Third , the theory suggests why legislators who pay too much attention to national policy making relative to local benefit-seeking have lower security in office . , The tablets are pale-orange and have a score line on both sides so that they can be halved . , One of the cases at issue was a suit brought by 26 states challenging the sweeping healthcare overhaul passed by Congress last year , a law that has been a rallying cry for conservative activists nationwide . , For follow-up treatment , the animal owner can administer the tablets to the dog . 
pipeline_tag: text-classification
inference: yes
base_model: sentence-transformers/paraphrase-mpnet-base-v2
model-index: name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
results: task: type: text-classification
name: Text Classification
dataset: name: Unknown
type: unknown
split: test
metrics: type: accuracy
value: 0.15474452554744525
name: Accuracy
verified: no
Likes: 0 | All-time downloads: 179
Created: 2023-12-14 14:33:12