Upload dataset_info.json
Browse files- dataset_info.json +70 -0
dataset_info.json
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{
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"builder_name": "imdb",
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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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"config_name": "plain_text",
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"dataset_size": 133190346,
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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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"download_checksums": {
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"http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz": {
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"num_bytes": 84125825,
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"checksum": "c40f74a18d3b61f90feba1e17730e0d38e8b97c05fde7008942e91923d1658fe"
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}
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},
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"download_size": 84125825,
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"features": {
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"text": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"label": {
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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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"homepage": "http://ai.stanford.edu/~amaas/data/sentiment/",
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"license": "",
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"post_processed": null,
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"post_processing_size": null,
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"size_in_bytes": 217316171,
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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": "imdb"
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},
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"test": {
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"name": "test",
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"num_bytes": 32650697,
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"num_examples": 25000,
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"dataset_name": "imdb"
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},
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"unsupervised": {
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"name": "unsupervised",
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"num_bytes": 67106814,
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"num_examples": 50000,
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"dataset_name": "imdb"
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}
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},
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"supervised_keys": null,
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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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"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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}
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