File size: 4,427 Bytes
8175ba7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 |
{"din0s--ccmatrix_en-it_lrs_backtranslated": {
"description": "CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\nWe show that margin-based bitext mining in LASER's multilingual sentence space can be applied to\nmonolingual corpora of billions of sentences to produce high quality aligned translation data.\nWe use thirty-two snapshots of a curated common crawl corpus [1] totaling 69 billion unique sentences.\nUsing one unified approach for 80 languages, we were able to mine 10.8 billion parallel sentences,\nout of which only 2.9 billion are aligned with English.\n\nIMPORTANT: Please cite reference [2][3] if you use this data.\n\n[1] Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli\n and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data\n\n[2] Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin,\n CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\n[3] Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines,\n Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky,\n Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin.\n Beyond English-Centric Multilingual Machine Translation\n \n90 languages, 1,197 bitexts\ntotal number of files: 90\ntotal number of tokens: 112.14G\ntotal number of sentence fragments: 7.37G\n\n\nCCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\nWe show that margin-based bitext mining in LASER's multilingual sentence space can be applied to\nmonolingual corpora of billions of sentences to produce high quality aligned translation data.\nWe use thirty-two snapshots of a curated common crawl corpus [1] totaling 69 billion unique sentences.\nUsing one unified approach for 80 languages, we were able to mine 10.8 billion parallel sentences,\nout of which only 2.9 billion are aligned with English.\n\nIMPORTANT: Please cite reference [2][3] if you use this data.\n\n[1] Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli\n and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data\n\n[2] Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin,\n CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\n[3] Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines,\n Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky,\n Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin.\n Beyond English-Centric Multilingual Machine Translation\n \n90 languages, 1,197 bitexts\ntotal number of files: 90\ntotal number of tokens: 112.14G\ntotal number of sentence fragments: 7.37G",
"citation": "Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data\n\n\nGuillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data",
"homepage": "https://opus.nlpl.eu/CCMatrix.php",
"license": "",
"features": {
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"translation": {
"languages": [
"en",
"it"
],
"id": null,
"_type": "Translation"
}
},
"post_processed": null,
"supervised_keys": null,
"task_templates": null,
"builder_name": null,
"config_name": null,
"version": null,
"splits": {
"train": {
"name": "train",
"num_bytes": 9544615,
"num_examples": 39000,
"dataset_name": "ccmatrix_en-it_lrs_backtranslated"
}
},
"download_checksums": null,
"download_size": 6544910,
"post_processing_size": null,
"dataset_size": 9544615,
"size_in_bytes": 16089525
}} |