Model: hojzas/proj4-match_permutations_substrings-lab1
Author: hojzas
Pipeline: text-classification
Library: setfit
Tags: setfit, safetensors, mpnet, sentence-transformers, text-classification, generated_from_setfit_trainer, dataset:hojzas/proj4-match_permutations_substrings-lab1, arxiv:2209.11055, base_model:sentence-transformers/all-mpnet-base-v2, base_model:finetune:sentence-transformers/all-mpnet-base-v2, 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-match_permutations_substrings-lab1
metrics: accuracy
widget:     counter = defaultdict(int)\n    for character in string:\n        counter[character] += 1\n    result = set()\n    for word in words:\n        word_counter = defaultdict(int)\n        for character in word:\n            word_counter[character] += 1\n        for key, count in word_counter.items():\n            if counter[key] < count:\n                break\n        else:\n            result.add(word)\n    return result,     perms = all_permutations_substrings(string)\n    return set([x for x in list(perms) + words if x in list(perms) and x in words]),     perms = all_permutations_substrings(string)\n    return set( perms.intersection(words)),     perms = all_permutations_substrings(string)\n    for x in perms:\n        words.append(x)\n    dupes = [x for n, x in enumerate(words) if x in words[:n]]  \n    return set(dupes),     perms = all_permutations_substrings(string)\n    to_return = []\n    for w in words:\n        if w in perms:\n            to_return.append(w)\n    to_return = set(to_return)\n    return to_return
pipeline_tag: text-classification
inference: yes
co2_eq_emissions: emissions: 1.8025910115185662
source: codecarbon
training_type: fine-tuning
on_cloud: no
cpu_model: Intel(R) Xeon(R) Silver 4314 CPU @ 2.40GHz
ram_total_size: 251.49161911010742
hours_used: 0.006
hardware_used: 4 x NVIDIA RTX A5000
base_model: sentence-transformers/all-mpnet-base-v2
Likes: 0 | All-time downloads: 183
Created: 2024-02-04 08:56:51