diff --git "a/dataset_infos.json" "b/dataset_infos.json" --- "a/dataset_infos.json" +++ "b/dataset_infos.json" @@ -26,13 +26,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "XNLI", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -58,6 +58,7 @@ } }, "download_size": 17865352, + "post_processing_size": null, "dataset_size": 30408803, "size_in_bytes": 48274155 }, @@ -105,13 +106,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tydiqa", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -141,6 +142,7 @@ } }, "download_size": 63621485, + "post_processing_size": null, "dataset_size": 57955068, "size_in_bytes": 121576553 }, @@ -188,13 +190,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "SQuAD", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -224,6 +226,7 @@ } }, "download_size": 35142551, + "post_processing_size": null, "dataset_size": 89789763, "size_in_bytes": 124932314 }, @@ -243,7 +246,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -264,13 +267,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.af", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -297,6 +300,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 1694073, "size_in_bytes": 1694073 }, @@ -316,7 +320,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -337,13 +341,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ar", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -370,6 +374,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 7090196, "size_in_bytes": 7090196 }, @@ -389,7 +394,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -410,13 +415,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.bg", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -443,6 +448,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 8702230, "size_in_bytes": 8702230 }, @@ -462,7 +468,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -483,13 +489,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.bn", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -516,6 +522,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 1903865, "size_in_bytes": 1903865 }, @@ -535,7 +542,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -556,13 +563,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.de", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -589,6 +596,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 8811426, "size_in_bytes": 8811426 }, @@ -608,7 +616,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -629,13 +637,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.el", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -662,6 +670,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 9486459, "size_in_bytes": 9486459 }, @@ -681,7 +690,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -702,13 +711,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.en", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -735,6 +744,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 7328751, "size_in_bytes": 7328751 }, @@ -754,7 +764,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -775,13 +785,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.es", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -808,6 +818,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 6217664, "size_in_bytes": 6217664 }, @@ -827,7 +838,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -848,13 +859,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.et", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -881,6 +892,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 6616949, "size_in_bytes": 6616949 }, @@ -900,7 +912,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -921,13 +933,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.eu", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -954,6 +966,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 6339963, "size_in_bytes": 6339963 }, @@ -973,7 +986,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -994,13 +1007,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.fa", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1027,6 +1040,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 7015870, "size_in_bytes": 7015870 }, @@ -1046,7 +1060,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1067,13 +1081,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.fi", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1100,6 +1114,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 7956188, "size_in_bytes": 7956188 }, @@ -1119,7 +1134,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1140,13 +1155,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.fr", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1173,6 +1188,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 6428893, "size_in_bytes": 6428893 }, @@ -1192,7 +1208,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1213,13 +1229,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.he", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1246,6 +1262,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 8776475, "size_in_bytes": 8776475 }, @@ -1265,7 +1282,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1286,13 +1303,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.hi", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1319,6 +1336,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 1320001, "size_in_bytes": 1320001 }, @@ -1338,7 +1356,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1359,13 +1377,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.hu", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1392,6 +1410,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 8325555, "size_in_bytes": 8325555 }, @@ -1411,7 +1430,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1432,13 +1451,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.id", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1465,6 +1484,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 5961385, "size_in_bytes": 5961385 }, @@ -1484,7 +1504,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1505,13 +1525,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.it", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1538,6 +1558,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 7267519, "size_in_bytes": 7267519 }, @@ -1557,7 +1578,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1578,13 +1599,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ja", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1611,6 +1632,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 23052660, "size_in_bytes": 23052660 }, @@ -1630,7 +1652,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1651,13 +1673,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.jv", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1684,6 +1706,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 45093, "size_in_bytes": 45093 }, @@ -1703,7 +1726,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1724,13 +1747,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ka", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1757,6 +1780,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 8011091, "size_in_bytes": 8011091 }, @@ -1776,7 +1800,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1797,13 +1821,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.kk", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1830,6 +1854,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 671681, "size_in_bytes": 671681 }, @@ -1849,7 +1874,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1870,13 +1895,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ko", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1903,6 +1928,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 8009040, "size_in_bytes": 8009040 }, @@ -1922,7 +1948,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -1943,13 +1969,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ml", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -1976,6 +2002,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 3309129, "size_in_bytes": 3309129 }, @@ -1995,7 +2022,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2016,13 +2043,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.mr", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -2049,6 +2076,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 1681822, "size_in_bytes": 1681822 }, @@ -2068,7 +2096,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2089,13 +2117,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ms", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -2122,6 +2150,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 3178657, "size_in_bytes": 3178657 }, @@ -2141,7 +2170,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2162,13 +2191,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.my", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -2195,6 +2224,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 106548, "size_in_bytes": 106548 }, @@ -2214,7 +2244,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2235,13 +2265,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.nl", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -2268,6 +2298,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 7584224, "size_in_bytes": 7584224 }, @@ -2287,7 +2318,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2308,13 +2339,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.pt", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -2341,6 +2372,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 6113883, "size_in_bytes": 6113883 }, @@ -2360,7 +2392,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2381,13 +2413,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ru", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -2414,6 +2446,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 7891953, "size_in_bytes": 7891953 }, @@ -2433,7 +2466,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2454,13 +2487,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.sw", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -2487,6 +2520,7 @@ }, "download_checksums": {}, "download_size": 0, + "post_processing_size": null, "dataset_size": 400674, "size_in_bytes": 400674 }, @@ -2506,7 +2540,7 @@ "id": null, "_type": "Sequence" }, - "ner_tags": { + "ner": { "feature": { "dtype": "string", "id": null, @@ -2527,13 +2561,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAN-X.ta", "version": { "version_str": "1.0.0", "description": "", - 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"datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -6936,6 +7026,7 @@ } }, "download_size": 75719050, + "post_processing_size": null, "dataset_size": 4282631, "size_in_bytes": 80001681 }, @@ -6983,13 +7074,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "MLQA.hi.hi", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -7015,6 +7106,7 @@ } }, "download_size": 75719050, + "post_processing_size": null, "dataset_size": 12947259, "size_in_bytes": 88666309 }, @@ -7057,13 +7149,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "XQuAD.ar", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -7083,6 +7175,7 @@ } }, "download_size": 1582988, + "post_processing_size": null, "dataset_size": 1722799, "size_in_bytes": 3305787 }, @@ -7125,13 +7218,13 @@ "_type": "Sequence" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "XQuAD.de", "version": { "version_str": "1.0.0", "description": "", - 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"datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -7763,6 +7865,7 @@ } }, "download_size": 729506, + "post_processing_size": null, "dataset_size": 1210763, "size_in_bytes": 1940269 }, @@ -7793,13 +7896,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "bucc18.de", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -7829,6 +7932,7 @@ } }, "download_size": 30719200, + "post_processing_size": null, "dataset_size": 2557103, "size_in_bytes": 33276303 }, @@ -7859,13 +7963,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "bucc18.fr", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -7895,6 +7999,7 @@ } }, "download_size": 22706544, + "post_processing_size": null, "dataset_size": 2274768, "size_in_bytes": 24981312 }, @@ -7925,13 +8030,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "bucc18.zh", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -7961,6 +8066,7 @@ } }, "download_size": 7114794, + "post_processing_size": null, "dataset_size": 467079, "size_in_bytes": 7581873 }, @@ -7991,13 +8097,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "bucc18.ru", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8027,6 +8133,7 @@ } }, "download_size": 41354312, + "post_processing_size": null, "dataset_size": 5335223, "size_in_bytes": 46689535 }, @@ -8052,13 +8159,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAWS-X.de", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8090,6 +8197,7 @@ } }, "download_size": 30282057, + "post_processing_size": null, "dataset_size": 13462086, "size_in_bytes": 43744143 }, @@ -8115,13 +8223,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAWS-X.en", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8153,6 +8261,7 @@ } }, "download_size": 30282057, + "post_processing_size": null, "dataset_size": 12786748, "size_in_bytes": 43068805 }, @@ -8178,13 +8287,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAWS-X.es", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8216,6 +8325,7 @@ } }, "download_size": 30282057, + "post_processing_size": null, "dataset_size": 13461223, "size_in_bytes": 43743280 }, @@ -8241,13 +8351,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAWS-X.fr", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8279,6 +8389,7 @@ } }, "download_size": 30282057, + "post_processing_size": null, "dataset_size": 13985654, "size_in_bytes": 44267711 }, @@ -8304,13 +8415,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAWS-X.ja", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8342,6 +8453,7 @@ } }, "download_size": 30282057, + "post_processing_size": null, "dataset_size": 15998067, "size_in_bytes": 46280124 }, @@ -8367,13 +8479,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAWS-X.ko", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8405,6 +8517,7 @@ } }, "download_size": 30282057, + "post_processing_size": null, "dataset_size": 14631422, "size_in_bytes": 44913479 }, @@ -8430,13 +8543,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "PAWS-X.zh", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8468,6 +8581,7 @@ } }, "download_size": 30282057, + "post_processing_size": null, "dataset_size": 11389470, "size_in_bytes": 41671527 }, @@ -8498,13 +8612,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.afr", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8512,7 +8626,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 142651, + "num_bytes": 179651, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8528,8 +8642,9 @@ } }, "download_size": 59635, - "dataset_size": 142651, - "size_in_bytes": 202286 + "post_processing_size": null, + "dataset_size": 179651, + "size_in_bytes": 239286 }, "tatoeba.ara": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8558,13 +8673,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.ara", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8572,7 +8687,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 155666, + "num_bytes": 192666, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8588,8 +8703,9 @@ } }, "download_size": 72650, - "dataset_size": 155666, - "size_in_bytes": 228316 + "post_processing_size": null, + "dataset_size": 192666, + "size_in_bytes": 265316 }, "tatoeba.ben": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8618,13 +8734,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.ben", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8632,7 +8748,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 174719, + "num_bytes": 211719, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8648,8 +8764,9 @@ } }, "download_size": 91703, - "dataset_size": 174719, - "size_in_bytes": 266422 + "post_processing_size": null, + "dataset_size": 211719, + "size_in_bytes": 303422 }, "tatoeba.bul": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8678,13 +8795,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.bul", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8692,7 +8809,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 185295, + "num_bytes": 222295, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8708,8 +8825,9 @@ } }, "download_size": 102279, - "dataset_size": 185295, - "size_in_bytes": 287574 + "post_processing_size": null, + "dataset_size": 222295, + "size_in_bytes": 324574 }, "tatoeba.deu": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8738,13 +8856,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.deu", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8752,7 +8870,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 188583, + "num_bytes": 225583, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8768,8 +8886,9 @@ } }, "download_size": 105567, - "dataset_size": 188583, - "size_in_bytes": 294150 + "post_processing_size": null, + "dataset_size": 225583, + "size_in_bytes": 331150 }, "tatoeba.cmn": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8798,13 +8917,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.cmn", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8812,7 +8931,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 151947, + "num_bytes": 188947, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8828,8 +8947,9 @@ } }, "download_size": 68931, - "dataset_size": 151947, - "size_in_bytes": 220878 + "post_processing_size": null, + "dataset_size": 188947, + "size_in_bytes": 257878 }, "tatoeba.ell": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8858,13 +8978,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.ell", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8872,7 +8992,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 161977, + "num_bytes": 198977, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8888,8 +9008,9 @@ } }, "download_size": 78961, - "dataset_size": 161977, - "size_in_bytes": 240938 + "post_processing_size": null, + "dataset_size": 198977, + "size_in_bytes": 277938 }, "tatoeba.est": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8918,13 +9039,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.est", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8932,7 +9053,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 142744, + "num_bytes": 179744, "num_examples": 1000, "dataset_name": "xtreme" } @@ -8948,8 +9069,9 @@ } }, "download_size": 59728, - "dataset_size": 142744, - "size_in_bytes": 202472 + "post_processing_size": null, + "dataset_size": 179744, + "size_in_bytes": 239472 }, "tatoeba.eus": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -8978,13 +9100,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.eus", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -8992,7 +9114,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 149084, + "num_bytes": 186084, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9008,8 +9130,9 @@ } }, "download_size": 66068, - "dataset_size": 149084, - "size_in_bytes": 215152 + "post_processing_size": null, + "dataset_size": 186084, + "size_in_bytes": 252152 }, "tatoeba.fin": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9038,13 +9161,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.fin", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9052,7 +9175,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 158685, + "num_bytes": 195685, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9068,8 +9191,9 @@ } }, "download_size": 75669, - "dataset_size": 158685, - "size_in_bytes": 234354 + "post_processing_size": null, + "dataset_size": 195685, + "size_in_bytes": 271354 }, "tatoeba.fra": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9098,13 +9222,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.fra", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9112,7 +9236,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 163034, + "num_bytes": 200034, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9128,8 +9252,9 @@ } }, "download_size": 80018, - "dataset_size": 163034, - "size_in_bytes": 243052 + "post_processing_size": null, + "dataset_size": 200034, + "size_in_bytes": 280052 }, "tatoeba.heb": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9158,13 +9283,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.heb", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9172,7 +9297,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 166516, + "num_bytes": 203516, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9188,8 +9313,9 @@ } }, "download_size": 83500, - "dataset_size": 166516, - "size_in_bytes": 250016 + "post_processing_size": null, + "dataset_size": 203516, + "size_in_bytes": 287016 }, "tatoeba.hin": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9218,13 +9344,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.hin", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9232,7 +9358,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 205574, + "num_bytes": 242574, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9248,8 +9374,9 @@ } }, "download_size": 122558, - "dataset_size": 205574, - "size_in_bytes": 328132 + "post_processing_size": null, + "dataset_size": 242574, + "size_in_bytes": 365132 }, "tatoeba.hun": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9278,13 +9405,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.hun", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9292,7 +9419,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 151905, + "num_bytes": 188905, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9308,8 +9435,9 @@ } }, "download_size": 68889, - "dataset_size": 151905, - "size_in_bytes": 220794 + "post_processing_size": null, + "dataset_size": 188905, + "size_in_bytes": 257794 }, "tatoeba.ind": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9338,13 +9466,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.ind", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9352,7 +9480,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 157860, + "num_bytes": 194860, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9368,8 +9496,9 @@ } }, "download_size": 74844, - "dataset_size": 157860, - "size_in_bytes": 232704 + "post_processing_size": null, + "dataset_size": 194860, + "size_in_bytes": 269704 }, "tatoeba.ita": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9398,13 +9527,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.ita", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9412,7 +9541,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 148849, + "num_bytes": 185849, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9428,8 +9557,9 @@ } }, "download_size": 65833, - "dataset_size": 148849, - "size_in_bytes": 214682 + "post_processing_size": null, + "dataset_size": 185849, + "size_in_bytes": 251682 }, "tatoeba.jav": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9458,13 +9588,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.jav", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9472,7 +9602,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 30944, + "num_bytes": 38529, "num_examples": 205, "dataset_name": "xtreme" } @@ -9488,8 +9618,9 @@ } }, "download_size": 13913, - "dataset_size": 30944, - "size_in_bytes": 44857 + "post_processing_size": null, + "dataset_size": 38529, + "size_in_bytes": 52442 }, "tatoeba.jpn": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9518,13 +9649,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.jpn", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9532,7 +9663,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 176099, + "num_bytes": 213099, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9548,8 +9679,9 @@ } }, "download_size": 93083, - "dataset_size": 176099, - "size_in_bytes": 269182 + "post_processing_size": null, + "dataset_size": 213099, + "size_in_bytes": 306182 }, "tatoeba.kat": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9578,13 +9710,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.kat", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9592,7 +9724,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 134094, + "num_bytes": 161696, "num_examples": 746, "dataset_name": "xtreme" } @@ -9608,8 +9740,9 @@ } }, "download_size": 72160, - "dataset_size": 134094, - "size_in_bytes": 206254 + "post_processing_size": null, + "dataset_size": 161696, + "size_in_bytes": 233856 }, "tatoeba.kaz": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9638,13 +9771,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.kaz", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9652,7 +9785,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 94919, + "num_bytes": 116194, "num_examples": 575, "dataset_name": "xtreme" } @@ -9668,8 +9801,9 @@ } }, "download_size": 47178, - "dataset_size": 94919, - "size_in_bytes": 142097 + "post_processing_size": null, + "dataset_size": 116194, + "size_in_bytes": 163372 }, "tatoeba.kor": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9698,13 +9832,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.kor", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9712,7 +9846,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 162155, + "num_bytes": 199155, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9728,8 +9862,9 @@ } }, "download_size": 79139, - "dataset_size": 162155, - "size_in_bytes": 241294 + "post_processing_size": null, + "dataset_size": 199155, + "size_in_bytes": 278294 }, "tatoeba.mal": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9758,13 +9893,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.mal", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9772,7 +9907,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 151754, + "num_bytes": 177173, "num_examples": 687, "dataset_name": "xtreme" } @@ -9788,8 +9923,9 @@ } }, "download_size": 94717, - "dataset_size": 151754, - "size_in_bytes": 246471 + "post_processing_size": null, + "dataset_size": 177173, + "size_in_bytes": 271890 }, "tatoeba.mar": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9818,13 +9954,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.mar", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9832,7 +9968,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 183558, + "num_bytes": 220558, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9848,8 +9984,9 @@ } }, "download_size": 100542, - "dataset_size": 183558, - "size_in_bytes": 284100 + "post_processing_size": null, + "dataset_size": 220558, + "size_in_bytes": 321100 }, "tatoeba.nld": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9878,13 +10015,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.nld", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9892,7 +10029,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 156279, + "num_bytes": 193279, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9908,8 +10045,9 @@ } }, "download_size": 73263, - "dataset_size": 156279, - "size_in_bytes": 229542 + "post_processing_size": null, + "dataset_size": 193279, + "size_in_bytes": 266542 }, "tatoeba.pes": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9938,13 +10076,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.pes", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -9952,7 +10090,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 176735, + "num_bytes": 213735, "num_examples": 1000, "dataset_name": "xtreme" } @@ -9968,8 +10106,9 @@ } }, "download_size": 93719, - "dataset_size": 176735, - "size_in_bytes": 270454 + "post_processing_size": null, + "dataset_size": 213735, + "size_in_bytes": 307454 }, "tatoeba.por": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -9998,13 +10137,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.por", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10012,7 +10151,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 158201, + "num_bytes": 195201, "num_examples": 1000, "dataset_name": "xtreme" } @@ -10028,8 +10167,9 @@ } }, "download_size": 75185, - "dataset_size": 158201, - "size_in_bytes": 233386 + "post_processing_size": null, + "dataset_size": 195201, + "size_in_bytes": 270386 }, "tatoeba.rus": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10058,13 +10198,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.rus", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10072,7 +10212,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 175488, + "num_bytes": 212488, "num_examples": 1000, "dataset_name": "xtreme" } @@ -10088,8 +10228,9 @@ } }, "download_size": 92472, - "dataset_size": 175488, - "size_in_bytes": 267960 + "post_processing_size": null, + "dataset_size": 212488, + "size_in_bytes": 304960 }, "tatoeba.spa": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10118,13 +10259,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.spa", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10132,7 +10273,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 155282, + "num_bytes": 192282, "num_examples": 1000, "dataset_name": "xtreme" } @@ -10148,8 +10289,9 @@ } }, "download_size": 72266, - "dataset_size": 155282, - "size_in_bytes": 227548 + "post_processing_size": null, + "dataset_size": 192282, + "size_in_bytes": 264548 }, "tatoeba.swh": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10178,13 +10320,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.swh", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10192,7 +10334,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 52853, + "num_bytes": 67283, "num_examples": 390, "dataset_name": "xtreme" } @@ -10208,8 +10350,9 @@ } }, "download_size": 20467, - "dataset_size": 52853, - "size_in_bytes": 73320 + "post_processing_size": null, + "dataset_size": 67283, + "size_in_bytes": 87750 }, "tatoeba.tam": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10238,13 +10381,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.tam", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10252,7 +10395,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 64938, + "num_bytes": 76297, "num_examples": 307, "dataset_name": "xtreme" } @@ -10268,8 +10411,9 @@ } }, "download_size": 39441, - "dataset_size": 64938, - "size_in_bytes": 104379 + "post_processing_size": null, + "dataset_size": 76297, + "size_in_bytes": 115738 }, "tatoeba.tgl": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10298,13 +10442,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.tgl", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10312,7 +10456,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 151154, + "num_bytes": 188154, "num_examples": 1000, "dataset_name": "xtreme" } @@ -10328,8 +10472,9 @@ } }, "download_size": 68138, - "dataset_size": 151154, - "size_in_bytes": 219292 + "post_processing_size": null, + "dataset_size": 188154, + "size_in_bytes": 256292 }, "tatoeba.tha": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10358,13 +10503,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.tha", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10372,7 +10517,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 108698, + "num_bytes": 128974, "num_examples": 548, "dataset_name": "xtreme" } @@ -10388,8 +10533,9 @@ } }, "download_size": 63198, - "dataset_size": 108698, - "size_in_bytes": 171896 + "post_processing_size": null, + "dataset_size": 128974, + "size_in_bytes": 192172 }, "tatoeba.tur": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10418,13 +10564,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.tur", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10432,7 +10578,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 154901, + "num_bytes": 191901, "num_examples": 1000, "dataset_name": "xtreme" } @@ -10448,8 +10594,9 @@ } }, "download_size": 71885, - "dataset_size": 154901, - "size_in_bytes": 226786 + "post_processing_size": null, + "dataset_size": 191901, + "size_in_bytes": 263786 }, "tatoeba.urd": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10478,13 +10625,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.urd", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10492,7 +10639,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 171728, + "num_bytes": 208728, "num_examples": 1000, "dataset_name": "xtreme" } @@ -10508,8 +10655,9 @@ } }, "download_size": 88712, - "dataset_size": 171728, - "size_in_bytes": 260440 + "post_processing_size": null, + "dataset_size": 208728, + "size_in_bytes": 297440 }, "tatoeba.vie": { "description": "his data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.\n\nFor each languages, we have selected 1000 English sentences and their translations, if available. Please check\nthis paper for a description of the languages, their families and scripts as well as baseline results.\n\nPlease note that the English sentences are not identical for all language pairs. This means that the results are\nnot directly comparable across languages. In particular, the sentences tend to have less variety for several\nlow-resource languages, e.g. \"Tom needed water\", \"Tom needs water\", \"Tom is getting water\", ...\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10538,13 +10686,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "tatoeba.vie", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10552,7 +10700,7 @@ "splits": { "validation": { "name": "validation", - "num_bytes": 174423, + "num_bytes": 211423, "num_examples": 1000, "dataset_name": "xtreme" } @@ -10568,8 +10716,9 @@ } }, "download_size": 91407, - "dataset_size": 174423, - "size_in_bytes": 265830 + "post_processing_size": null, + "dataset_size": 211423, + "size_in_bytes": 302830 }, "udpos.Afrikaans": { "description": "Universal Dependencies (UD) is a framework for consistent annotation of grammar (parts of speech, morphological\nfeatures, and syntactic dependencies) across different human languages. UD is an open community effort with over 200\ncontributors producing more than 100 treebanks in over 70 languages. If you’re new to UD, you should start by reading\nthe first part of the Short Introduction and then browsing the annotation guidelines.\n\nThe Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of\nthe cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages\n(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of\nsyntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks,\nand availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil\n(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the\nNiger-Congo languages Swahili and Yoruba, spoken in Africa.\n", @@ -10588,13 +10737,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Afrikaans", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10626,6 +10775,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 822426, "size_in_bytes": 356039107 }, @@ -10646,13 +10796,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Arabic", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10684,6 +10834,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 6629722, "size_in_bytes": 361846403 }, @@ -10704,13 +10855,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Basque", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10742,6 +10893,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 2140325, "size_in_bytes": 357357006 }, @@ -10762,13 +10914,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Bulgarian", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10800,6 +10952,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 3269254, "size_in_bytes": 358485935 }, @@ -10820,13 +10973,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Dutch", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10858,6 +11011,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 5081762, "size_in_bytes": 360298443 }, @@ -10878,13 +11032,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.English", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10916,6 +11070,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 8367407, "size_in_bytes": 363584088 }, @@ -10936,13 +11091,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Estonian", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -10974,6 +11129,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 8226527, "size_in_bytes": 363443208 }, @@ -10994,13 +11150,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Finnish", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11032,6 +11188,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 7025945, "size_in_bytes": 362242626 }, @@ -11052,13 +11209,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.French", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11090,6 +11247,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 12609554, "size_in_bytes": 367826235 }, @@ -11110,13 +11268,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.German", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11148,6 +11306,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 65581818, "size_in_bytes": 420798499 }, @@ -11168,13 +11327,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Greek", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11206,6 +11365,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 10666610, "size_in_bytes": 365883291 }, @@ -11226,13 +11386,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Hebrew", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11264,6 +11424,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 3604613, "size_in_bytes": 358821294 }, @@ -11284,13 +11445,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Hindi", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11322,6 +11483,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 8724457, "size_in_bytes": 363941138 }, @@ -11342,13 +11504,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Hungarian", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11380,6 +11542,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 762496, "size_in_bytes": 355979177 }, @@ -11400,13 +11563,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Indonesian", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11438,6 +11601,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 2448695, "size_in_bytes": 357665376 }, @@ -11458,13 +11622,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Italian", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11496,6 +11660,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 13799190, "size_in_bytes": 369015871 }, @@ -11516,13 +11681,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Japanese", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11554,6 +11719,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 3790638, "size_in_bytes": 359007319 }, @@ -11574,13 +11740,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Kazakh", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11606,6 +11772,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 235882, "size_in_bytes": 355452563 }, @@ -11626,13 +11793,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Korean", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11664,6 +11831,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 9002475, "size_in_bytes": 364219156 }, @@ -11684,13 +11852,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Chinese", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11722,6 +11890,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 5823729, "size_in_bytes": 361040410 }, @@ -11742,13 +11911,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Marathi", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11780,6 +11949,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 82223, "size_in_bytes": 355298904 }, @@ -11800,13 +11970,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Persian", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11838,6 +12008,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 2996381, "size_in_bytes": 358213062 }, @@ -11858,13 +12029,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Portuguese", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -11896,6 +12067,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 9649171, "size_in_bytes": 364865852 }, @@ -11916,13 +12088,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Russian", "version": { "version_str": "1.0.0", "description": "", - 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"datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -12116,6 +12291,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 338538, "size_in_bytes": 355555219 }, @@ -12136,13 +12312,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Telugu", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -12174,6 +12350,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 166170, "size_in_bytes": 355382851 }, @@ -12194,13 +12371,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Thai", "version": { "version_str": "1.0.0", "description": "", - "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0 @@ -12220,6 +12397,7 @@ } }, "download_size": 355216681, + "post_processing_size": null, "dataset_size": 548479, "size_in_bytes": 355765160 }, @@ -12240,13 +12418,13 @@ "_type": "Value" } }, + "post_processed": null, "supervised_keys": null, "builder_name": "xtreme", "config_name": "udpos.Turkish", "version": { "version_str": "1.0.0", "description": "", - 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