Datasets:
Tasks:
Text Classification
Sub-tasks:
natural-language-inference
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
Update files from the datasets library (from 1.2.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.2.0
- dataset_infos.json +1 -1
- dummy/plain_text/1.0.0/dummy_data.zip +2 -2
- hans.py +19 -1
dataset_infos.json
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{"plain_text": {"description": "The HANS dataset is an NLI evaluation set that tests specific hypotheses about invalid heuristics that NLI models are likely to learn.\n", "citation": "@article{DBLP:journals/corr/abs-1902-01007,\n author = {R. Thomas McCoy and\n Ellie Pavlick and\n Tal Linzen},\n title = {Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural\n Language Inference},\n journal = {CoRR},\n volume = {abs/1902.01007},\n year = {2019},\n url = {http://arxiv.org/abs/1902.01007},\n archivePrefix = {arXiv},\n eprint = {1902.01007},\n timestamp = {Tue, 21 May 2019 18:03:36 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-1902-01007.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/tommccoy1/hans", "license": "", "features": {"premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["entailment", "non-entailment"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}, "validation": {}}}, "supervised_keys": null, "builder_name": "hans", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "
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{"plain_text": {"description": "The HANS dataset is an NLI evaluation set that tests specific hypotheses about invalid heuristics that NLI models are likely to learn.\n", "citation": "@article{DBLP:journals/corr/abs-1902-01007,\n author = {R. Thomas McCoy and\n Ellie Pavlick and\n Tal Linzen},\n title = {Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural\n Language Inference},\n journal = {CoRR},\n volume = {abs/1902.01007},\n year = {2019},\n url = {http://arxiv.org/abs/1902.01007},\n archivePrefix = {arXiv},\n eprint = {1902.01007},\n timestamp = {Tue, 21 May 2019 18:03:36 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-1902-01007.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/tommccoy1/hans", "license": "", "features": {"premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["entailment", "non-entailment"], "names_file": null, "id": null, "_type": "ClassLabel"}, "parse_premise": {"dtype": "string", "id": null, "_type": "Value"}, "parse_hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "binary_parse_premise": {"dtype": "string", "id": null, "_type": "Value"}, "binary_parse_hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "heuristic": {"dtype": "string", "id": null, "_type": "Value"}, "subcase": {"dtype": "string", "id": null, "_type": "Value"}, "template": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}, "validation": {}}}, "supervised_keys": null, "builder_name": "hans", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 15916371, "num_examples": 30000, "dataset_name": "hans"}, "validation": {"name": "validation", "num_bytes": 15893137, "num_examples": 30000, "dataset_name": "hans"}}, "download_checksums": {"https://raw.githubusercontent.com/tommccoy1/hans/master/heuristics_train_set.txt": {"num_bytes": 15485296, "checksum": "49245bd5fdb0b185dcbfbf48f0f16513c62ad5bc9fad0b8800dc48d6818ee5cf"}, "https://raw.githubusercontent.com/tommccoy1/hans/master/heuristics_evaluation_set.txt": {"num_bytes": 15462062, "checksum": "c55b62feef9913070e88f38938dc2492018c945ac81f70139346472494124e79"}}, "download_size": 30947358, "post_processing_size": 0, "dataset_size": 31809508, "size_in_bytes": 62756866}}
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dummy/plain_text/1.0.0/dummy_data.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:fbc6b4f4ab76a3cddfa874134b1daf4c9f77c8c1eccfcaea5b06070357b066a7
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size 1295
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hans.py
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@@ -76,6 +76,13 @@ class Hans(datasets.GeneratorBasedBuilder):
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"premise": datasets.Value("string"),
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"hypothesis": datasets.Value("string"),
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"label": datasets.features.ClassLabel(names=["entailment", "non-entailment"]),
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}
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),
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# No default supervised_keys (as we have to pass both premise
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if split_line[0] == "-":
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continue
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# Works for both splits even though dev has some extra human labels.
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yield idx, {
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"premise": datasets.Value("string"),
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"hypothesis": datasets.Value("string"),
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"label": datasets.features.ClassLabel(names=["entailment", "non-entailment"]),
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"parse_premise": datasets.Value("string"),
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"parse_hypothesis": datasets.Value("string"),
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"binary_parse_premise": datasets.Value("string"),
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"binary_parse_hypothesis": datasets.Value("string"),
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"heuristic": datasets.Value("string"),
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"subcase": datasets.Value("string"),
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"template": datasets.Value("string"),
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}
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),
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# No default supervised_keys (as we have to pass both premise
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if split_line[0] == "-":
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continue
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# Works for both splits even though dev has some extra human labels.
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yield idx, {
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"premise": split_line[5],
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"hypothesis": split_line[6],
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"label": split_line[0],
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"binary_parse_premise": split_line[1],
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"binary_parse_hypothesis": split_line[2],
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"parse_premise": split_line[3],
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"parse_hypothesis": split_line[4],
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"heuristic": split_line[8],
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"subcase": split_line[9],
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"template": split_line[10],
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}
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