Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
Tags:
License:
davzoku commited on
Commit
f9c5c50
1 Parent(s): c9f4562

Convert dataset to Parquet

Browse files
README.md CHANGED
@@ -31,16 +31,25 @@ dataset_info:
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  '1': pos
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  splits:
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  - name: train
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  - name: validation
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  num_examples: 1066
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  - name: test
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  num_examples: 1066
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- download_size: 487770
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- dataset_size: 1345461
 
 
 
 
 
 
 
 
 
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  train-eval-index:
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  - config: default
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  task: text-classification
 
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  '1': pos
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  splits:
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  - name: train
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+ num_bytes: 1074806
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  - name: validation
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  num_examples: 1066
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  - name: test
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  num_examples: 1066
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+ download_size: 881052
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+ configs:
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: validation
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+ path: data/validation-*
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+ - split: test
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+ path: data/test-*
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  train-eval-index:
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  - config: default
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  task: text-classification
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dataset_infos.json CHANGED
@@ -1 +1,60 @@
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- {"default": {"description": "Movie Review Dataset.\nThis is a dataset of containing 5,331 positive and 5,331 negative processed\nsentences from Rotten Tomatoes movie reviews. This data was first used in Bo\nPang and Lillian Lee, ``Seeing stars: Exploiting class relationships for\nsentiment categorization with respect to rating scales.'', Proceedings of the\nACL, 2005.\n", "citation": "@InProceedings{Pang+Lee:05a,\n author = {Bo Pang and Lillian Lee},\n title = {Seeing stars: Exploiting class relationships for sentiment\n categorization with respect to rating scales},\n booktitle = {Proceedings of the ACL},\n year = 2005\n}\n", "homepage": "http://www.cs.cornell.edu/people/pabo/movie-review-data/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["neg", "pos"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "", "output": ""}, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label", "labels": ["neg", "pos"]}], "builder_name": "rotten_tomatoes_movie_review", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1074810, "num_examples": 8530, "dataset_name": "rotten_tomatoes_movie_review"}, "validation": {"name": "validation", "num_bytes": 134679, "num_examples": 1066, "dataset_name": "rotten_tomatoes_movie_review"}, "test": {"name": "test", "num_bytes": 135972, "num_examples": 1066, "dataset_name": "rotten_tomatoes_movie_review"}}, "download_checksums": {"https://storage.googleapis.com/seldon-datasets/sentence_polarity_v1/rt-polaritydata.tar.gz": {"num_bytes": 487770, "checksum": "a05befe52aafda71d458d188a1c54506a998b1308613ba76bbda2e5029409ce9"}}, "download_size": 487770, "post_processing_size": null, "dataset_size": 1345461, "size_in_bytes": 1833231}}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "default": {
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+ "description": "Movie Review Dataset.\nThis is a dataset of containing 5,331 positive and 5,331 negative processed\nsentences from Rotten Tomatoes movie reviews. This data was first used in Bo\nPang and Lillian Lee, ``Seeing stars: Exploiting class relationships for\nsentiment categorization with respect to rating scales.'', Proceedings of the\nACL, 2005.\n",
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+ "citation": "@InProceedings{Pang+Lee:05a,\n author = {Bo Pang and Lillian Lee},\n title = {Seeing stars: Exploiting class relationships for sentiment\n categorization with respect to rating scales},\n booktitle = {Proceedings of the ACL},\n year = 2005\n}\n",
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