{"version":"1.0","provider_name":"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8","provider_url":"https:\/\/atmokpo.com\/w","author_name":"root","author_url":"https:\/\/atmokpo.com\/w\/author\/root\/","title":"Hugging Face Transformers Utilization Course, BERT Ensemble Learning - Defining Custom Dataset - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"czjPxKDleX\"><a href=\"https:\/\/atmokpo.com\/w\/36085\/\">Hugging Face Transformers Utilization Course, BERT Ensemble Learning &#8211; Defining Custom Dataset<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/atmokpo.com\/w\/36085\/embed\/#?secret=czjPxKDleX\" width=\"600\" height=\"338\" title=\"&#8220;Hugging Face Transformers Utilization Course, BERT Ensemble Learning &#8211; Defining Custom Dataset&#8221; &#8212; \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" data-secret=\"czjPxKDleX\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/atmokpo.com\/w\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"Introduction Deep learning has brought about innovations in the field of Natural Language Processing (NLP) in recent years. In particular, the BERT (Bidirectional Encoder Representations from Transformers) model demonstrates powerful performance in understanding context and has achieved state-of-the-art results across various NLP tasks. This article will detail how to implement ensemble learning of the BERT &hellip; \ub354 \ubcf4\uae30 \"\""}