Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
100K - 1M
License:
Commit
•
2fa85f9
1
Parent(s):
1087fc1
Delete legacy dataset_infos.json
Browse files- dataset_infos.json +0 -60
dataset_infos.json
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{
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"plain_text": {
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"description": "Large Movie Review Dataset.\nThis is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well.",
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"citation": "@InProceedings{maas-EtAl:2011:ACL-HLT2011,\n author = {Maas, Andrew L. and Daly, Raymond E. and Pham, Peter T. and Huang, Dan and Ng, Andrew Y. and Potts, Christopher},\n title = {Learning Word Vectors for Sentiment Analysis},\n booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},\n month = {June},\n year = {2011},\n address = {Portland, Oregon, USA},\n publisher = {Association for Computational Linguistics},\n pages = {142--150},\n url = {http://www.aclweb.org/anthology/P11-1015}\n}\n",
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"homepage": "http://ai.stanford.edu/~amaas/data/sentiment/",
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"license": "",
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"features": {
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"text": {
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"dtype": "string",
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"_type": "Value"
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},
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"label": {
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"names": [
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"neg",
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"pos"
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],
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"_type": "ClassLabel"
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}
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},
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"task_templates": [
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{
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"task": "text-classification",
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"label_column": "label"
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}
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],
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"builder_name": "imdb",
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"dataset_name": "imdb",
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"config_name": "plain_text",
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"version": {
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"version_str": "1.0.0",
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"description": "",
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"major": 1,
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"minor": 0,
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"patch": 0
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},
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 33432823,
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"num_examples": 25000,
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"dataset_name": null
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},
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"test": {
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"name": "test",
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"num_bytes": 32650685,
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"num_examples": 25000,
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"dataset_name": null
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},
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"unsupervised": {
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"name": "unsupervised",
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"num_bytes": 67106794,
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"num_examples": 50000,
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"dataset_name": null
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}
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},
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"download_size": 83446840,
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"dataset_size": 133190302,
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"size_in_bytes": 216637142
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}
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}
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