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{"mariosasko--test_push_to_hub": { |
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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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}, |
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"num_classes": 2, |
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"names": [ |
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"neg", |
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"pos" |
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], |
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"id": null, |
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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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"text_column": "text", |
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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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"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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}, |
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"splits": { |
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"train": { |
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"name": "train", |
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"num_bytes": 33432835, |
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"num_examples": 25000, |
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"dataset_name": "test_push_to_hub" |
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} |
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"dataset_size": 33432835, |
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"size_in_bytes": 45687846 |
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}} |