TextForge Datasets

117 NLP Datasets for AutoML Development

@kaggle.shehansaleem_textforge_datasets

Table List

1 table(50.28 KB)

Trials Results

@kaggle.shehansaleem_textforge_datasets.trials_results

50.28 KB
702 rows
10 columns

dataset Dataset	model Model	accuracy Accuracy	precision Precision	recall Recall	f1_score F1 Score	size Size	load_time Load Time	time_predict Time Predict	time_train Time Train
20news-18828_train.csv	Albert	0.8466985307	0.8443977255	0.8427166056	0.8425503579	26358	3.108639717	26.1808672	753.8527129
20news-18828_train.csv	BERT Base Uncased	0.8874137015	0.8860098009	0.8834676848	0.8838349294	26358	3.07623744	20.56143808	749.9017155
20news-18828_train.csv	BOW with Random Forest	0.80456718	0.8136820542	0.801681479	0.8050683304	26358	3.07623744	1.862942457	18.60066962
20news-18828_train.csv	DistilBert	0.7750044256	0.7455316208	0.7603013806	0.7476445281	26358	3.108639717	17.3398757	380.5241981
20news-18828_train.csv	Tfidf with Logistic Regression	0.9479474922	0.9490305139	0.9456042022	0.9469546976	26358	4.459498167	2.536770105	2.925765276
20news-18828_train.csv	XLNet	0.8911311737	0.8885773713	0.8880347707	0.8880341359	26358	3.108639717	36.11518121	753.8527129
Deflate_train.csv	Albert	0.6244343891	0.5489104608	0.5177223178	0.5120254506	16500	0.235170126	15.24933052	469.4820802
Deflate_train.csv	BERT Base Uncased	0.6252828054	0.5682826864	0.5344389867	0.5419841549	16500	0.2401731014	16.05196762	444.4098995
Deflate_train.csv	BOW with Random Forest	0.5746606335	0.5872336236	0.4216703296	0.4461359844	16500	0.2401731014	3.899243116	7.946478844
Deflate_train.csv	DistilBert	0.5789027149	0.4286541971	0.4355483303	0.4293044632	16500	0.235170126	8.926192284	214.2019985


CREATE TABLE trials_results (
  "dataset" VARCHAR,
  "model" VARCHAR,
  "accuracy" DOUBLE,
  "precision" DOUBLE,
  "recall" DOUBLE,
  "f1_score" DOUBLE,
  "size" BIGINT,
  "load_time" DOUBLE,
  "time_predict" DOUBLE,
  "time_train" DOUBLE
);