Rename gem_id and gem_parent_id to match convention in source files
Browse files- dataset_infos.json +1 -1
- mlsum.py +2 -2
dataset_infos.json
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{"de": {"description": "This is the MLSUM subset of the GEM benchmark. MLSUM is the first large-scale MultiLingual SUMmarization dataset.\nObtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.\nTogether with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.\nWe report cross-lingual comparative analyses based on state-of-the-art systems.\nThese highlight existing biases which motivate the use of a multi-lingual dataset.\n", "citation": "@article{scialom2020mlsum,\n title={MLSUM: The Multilingual Summarization Corpus},\n author={Scialom, Thomas and Dray, Paul-Alexis and Lamprier, Sylvain and Piwowarski, Benjamin and Staiano, Jacopo},\n journal={arXiv preprint arXiv:2004.14900},\n year={2020}\n}\n", "homepage": "", "license": "", "features": {"gem_id": {"dtype": "string", "id": null, "_type": "Value"}, "gem_parent_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "topic": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"dtype": "string", "id": null, "_type": "Value"}, "references": [{"dtype": "string", "id": null, "_type": "Value"}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "mlsum", "config_name": "de", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes":
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{"de": {"description": "This is the MLSUM subset of the GEM benchmark. MLSUM is the first large-scale MultiLingual SUMmarization dataset.\nObtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.\nTogether with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.\nWe report cross-lingual comparative analyses based on state-of-the-art systems.\nThese highlight existing biases which motivate the use of a multi-lingual dataset.\n", "citation": "@article{scialom2020mlsum,\n title={MLSUM: The Multilingual Summarization Corpus},\n author={Scialom, Thomas and Dray, Paul-Alexis and Lamprier, Sylvain and Piwowarski, Benjamin and Staiano, Jacopo},\n journal={arXiv preprint arXiv:2004.14900},\n year={2020}\n}\n", "homepage": "", "license": "", "features": {"gem_id": {"dtype": "string", "id": null, "_type": "Value"}, "gem_parent_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "topic": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"dtype": "string", "id": null, "_type": "Value"}, "references": [{"dtype": "string", "id": null, "_type": "Value"}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "mlsum", "config_name": "de", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 858060337, "num_examples": 220748, "dataset_name": "mlsum"}, "validation": {"name": "validation", "num_bytes": 49712791, "num_examples": 11392, "dataset_name": "mlsum"}, "test": {"name": "test", "num_bytes": 49146354, "num_examples": 10695, "dataset_name": "mlsum"}, "challenge_train_sample": {"name": "challenge_train_sample", "num_bytes": 1891220, "num_examples": 500, "dataset_name": "mlsum"}, "challenge_validation_sample": {"name": "challenge_validation_sample", "num_bytes": 2199723, "num_examples": 500, "dataset_name": "mlsum"}, "challenge_test_covid": {"name": "challenge_test_covid", "num_bytes": 19771285, "num_examples": 5058, "dataset_name": "mlsum"}}, "download_checksums": {"https://gitlab.lip6.fr/scialom/mlsum_data/-/raw/master/MLSUM/de_train.zip": {"num_bytes": 311059697, "checksum": "88e788437bae48af6b3d18a554af4b2794cc6143a137df3f56daa91a37e3ea7e"}, "https://gitlab.lip6.fr/scialom/mlsum_data/-/raw/master/MLSUM/de_val.zip": {"num_bytes": 17771216, "checksum": "732620c32e1d3f393ee3193f57f1217d8549499eb4906e144252aaab39aa910b"}, "https://gitlab.lip6.fr/scialom/mlsum_data/-/raw/master/MLSUM/de_test.zip": {"num_bytes": 17741147, "checksum": "447e3b1839ab94d5700cc2aedc0b52521404865b2589656acc90a654ed0de4ff"}, "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_mlsum_bad_ids_fixed.json": {"num_bytes": 784429, "checksum": "7d1b5c340329da32b3a6c1b880e9d72b5193eb0782bc03261e4eaee08c3d5b64"}, "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_challenge_sets/mlsum_de.zip": {"num_bytes": 15427039, "checksum": "7cc6751d7a76e833e0db27ce0b06a50be4df43dfd5d5284dd11888439a126310"}}, "download_size": 362783528, "post_processing_size": null, "dataset_size": 980781710, "size_in_bytes": 1343565238}, "es": {"description": "This is the MLSUM subset of the GEM benchmark. MLSUM is the first large-scale MultiLingual SUMmarization dataset.\nObtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish.\nTogether with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community.\nWe report cross-lingual comparative analyses based on state-of-the-art systems.\nThese highlight existing biases which motivate the use of a multi-lingual dataset.\n", "citation": "@article{scialom2020mlsum,\n title={MLSUM: The Multilingual Summarization Corpus},\n author={Scialom, Thomas and Dray, Paul-Alexis and Lamprier, Sylvain and Piwowarski, Benjamin and Staiano, Jacopo},\n journal={arXiv preprint arXiv:2004.14900},\n year={2020}\n}\n", "homepage": "", "license": "", "features": {"gem_id": {"dtype": "string", "id": null, "_type": "Value"}, "gem_parent_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "topic": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"dtype": "string", "id": null, "_type": "Value"}, "references": [{"dtype": "string", "id": null, "_type": "Value"}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "mlsum", "config_name": "es", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1211240956, "num_examples": 259888, "dataset_name": "mlsum"}, "validation": {"name": "validation", "num_bytes": 51611723, "num_examples": 9977, "dataset_name": "mlsum"}, "test": {"name": "test", "num_bytes": 72117564, "num_examples": 13366, "dataset_name": "mlsum"}, "challenge_train_sample": {"name": "challenge_train_sample", "num_bytes": 2363443, "num_examples": 500, "dataset_name": "mlsum"}, "challenge_validation_sample": {"name": "challenge_validation_sample", "num_bytes": 2655596, "num_examples": 500, "dataset_name": "mlsum"}, "challenge_test_covid": {"name": "challenge_test_covid", "num_bytes": 13576624, "num_examples": 1938, "dataset_name": "mlsum"}}, "download_checksums": {"https://gitlab.lip6.fr/scialom/mlsum_data/-/raw/master/MLSUM/es_train.zip": {"num_bytes": 466443036, "checksum": "a01f4b4b873aa6cdeae15952a22ede2146734d0b60e7297470a35956507c863a"}, "https://gitlab.lip6.fr/scialom/mlsum_data/-/raw/master/MLSUM/es_val.zip": {"num_bytes": 19483214, "checksum": "e38fce9950008ec4b48963692891c4c94d51a1e307286fb596e093aeb1230c92"}, "https://gitlab.lip6.fr/scialom/mlsum_data/-/raw/master/MLSUM/es_test.zip": {"num_bytes": 27386169, "checksum": "177cfcf358bc4aa9bce2753b8e9de4f6eb41d2c30b1a99ef29d64e70537a1c0d"}, "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_mlsum_bad_ids_fixed.json": {"num_bytes": 784429, "checksum": "7d1b5c340329da32b3a6c1b880e9d72b5193eb0782bc03261e4eaee08c3d5b64"}, "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_challenge_sets/mlsum_es.zip": {"num_bytes": 11524578, "checksum": "a254972fef695970aea0370be64fed6aec8c8b760f238fabd0e8f363bf8274cd"}}, "download_size": 525621426, "post_processing_size": null, "dataset_size": 1353565906, "size_in_bytes": 1879187332}}
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mlsum.py
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@@ -136,8 +136,8 @@ class Mlsum(datasets.GeneratorBasedBuilder):
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else:
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id_ += 1
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yield id_, {
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"gem_id": f"{self.config.name}-{split}-{id_}",
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"gem_parent_id": f"{self.config.name}-{split}-{id_}",
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"text": data["text"],
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"target": data["summary"],
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"references": [] if split == "train" else [data["summary"]],
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else:
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id_ += 1
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yield id_, {
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"gem_id": f"mlsum_{self.config.name}-{split}-{id_}",
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"gem_parent_id": f"mlsum_{self.config.name}-{split}-{id_}",
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"text": data["text"],
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"target": data["summary"],
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"references": [] if split == "train" else [data["summary"]],
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