stats

dataset_stats.py

@@ -1,9 +1,4 @@
-import os
-import json
-from os.path import join as pj
-from glob import glob
 from statistics import mean
-
 import pandas as pd
 from datasets import load_dataset
 
@@ -13,10 +8,10 @@ def count_word(text):
 
 
 if __name__ == '__main__':
-    data = ["chemprot", "citation_intent", "hyperpartisan_news", "rct-sample", "sciie"]
+    data = ["chemprot", "citation_intent", "hyperpartisan_news", "rct-sample", "sciie", "amcd"]
     stats = {}
     for d in data:
-        _data = load_dataset('', d)
+        _data = load_dataset('asahi417/multi_domain_document_classification', d)
         stats[d] = {
             'word/validation': mean([count_word(k['text']) for k in _data['validation']]),
             'word/test': mean([count_word(k['text']) for k in _data['test']]),

stats.csv

@@ -1,7 +1,7 @@
-,chemprot,citation_intent,hyperpartisan_news,rct-sample,sciie
-word/validation,32,40,502,26,32
-word/test,32,42,612,26,32
-word/train,31,42,536,26,32
-instance/dev,2427,114,64,30212,455
-instance/test,3469,139,65,30135,974
-instance/train,4169,1688,516,500,3219
+,chemprot,citation_intent,hyperpartisan_news,rct-sample,sciie,amcd
+word/validation,32,40,502,26,32,20
+word/test,32,42,612,26,32,19
+word/train,31,42,536,26,32,19
+instance/dev,2427,114,64,30212,455,666
+instance/test,3469,139,65,30135,974,1334
+instance/train,4169,1688,516,500,3219,8000