Model: hojzas/setfit-proj4-label
Author: hojzas
Pipeline: text-classification
Library: setfit
Tags: setfit, safetensors, mpnet, sentence-transformers, text-classification, generated_from_setfit_trainer, dataset:hojzas/proj4-label, arxiv:2209.11055, base_model:sentence-transformers/all-mpnet-base-v2, base_model:finetune:sentence-transformers/all-mpnet-base-v2, model-index, co2_eq_emissions, region:us
Base models (finetune): id: sentence-transformers/all-mpnet-base-v2
Card metadata: library_name: setfit
tags: setfit, sentence-transformers, text-classification, generated_from_setfit_trainer
datasets: hojzas/proj4-label
metrics: accuracy
widget:     perms = all_permutations_substrings(string)
    
return perms.intersection(words),     perms = all_permutations_substrings(string)
return {i for i in words if i in perms},     perms = all_permutations_substrings(string)
return {word for word in words if hash(word) in {hash(looking) for looking in perms}},     perms = all_permutations_substrings(string)
res = [x for x in list(perms) + words if x in list(perms) and x in words]
return  set(res),     perms = all_permutations_substrings(string)
    
if set(words) & set(perms):
    res = (set(words) & set(perms))
pipeline_tag: text-classification
inference: yes
co2_eq_emissions: emissions: 0.30176603615895614
source: codecarbon
training_type: fine-tuning
on_cloud: no
cpu_model: Intel(R) Xeon(R) Silver 4314 CPU @ 2.40GHz
ram_total_size: 251.49160385131836
hours_used: 0.006
base_model: sentence-transformers/all-mpnet-base-v2
model-index: name: SetFit with sentence-transformers/all-mpnet-base-v2
results: task: type: text-classification
name: Text Classification
dataset: name: hojzas/proj4-label
type: hojzas/proj4-label
split: test
metrics: type: accuracy
value: 0.9375
name: Accuracy
verified: no
Likes: 0 | All-time downloads: 11
Created: 2024-01-26 17:08:20