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{"kmyoo--glue-mnli-tiny": {"description": "GLUE, the General Language Understanding Evaluation benchmark\n(https://gluebenchmark.com/) is a collection of resources for training,\nevaluating, and analyzing natural language understanding systems.\n\n", "citation": "@InProceedings{N18-1101,\n author = \"Williams, Adina\n and Nangia, Nikita\n and Bowman, Samuel\",\n title = \"A Broad-Coverage Challenge Corpus for\n Sentence Understanding through Inference\",\n booktitle = \"Proceedings of the 2018 Conference of\n the North American Chapter of the\n Association for Computational Linguistics:\n Human Language Technologies, Volume 1 (Long\n Papers)\",\n year = \"2018\",\n publisher = \"Association for Computational Linguistics\",\n pages = \"1112--1122\",\n location = \"New Orleans, Louisiana\",\n url = \"http://aclweb.org/anthology/N18-1101\"\n}\n@article{bowman2015large,\n title={A large annotated corpus for learning natural language inference},\n author={Bowman, Samuel R and Angeli, Gabor and Potts, Christopher and Manning, Christopher D},\n journal={arXiv preprint arXiv:1508.05326},\n year={2015}\n}\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R.},\n note={In the Proceedings of ICLR.},\n year={2019}\n}\n", "homepage": "http://www.nyu.edu/projects/bowman/multinli/", "license": "", "features": {"premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["entailment", "neutral", "contradiction"], "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "glue", "config_name": "mnli", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 19001.595611939843, "num_examples": 100, "dataset_name": "glue-mnli-tiny"}, "validation_matched": {"name": "validation_matched", "num_bytes": 18683.4742740703, "num_examples": 100, "dataset_name": "glue-mnli-tiny"}, "validation_mismatched": {"name": "validation_mismatched", "num_bytes": 19825.376322213182, "num_examples": 100, "dataset_name": "glue-mnli-tiny"}, "test_matched": {"name": "test_matched", "num_bytes": 18871.518987341773, "num_examples": 100, "dataset_name": "glue-mnli-tiny"}, "test_mismatched": {"name": "test_mismatched", "num_bytes": 19810.12491114045, "num_examples": 100, "dataset_name": "glue-mnli-tiny"}}, "download_checksums": null, "download_size": 83835, "post_processing_size": null, "dataset_size": 96192.09010670554, "size_in_bytes": 180027.09010670555}} |