Update parquet files

.gitattributes

@@ -1,82 +0,0 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zstandard filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
-*.sam filter=lfs diff=lfs merge=lfs -text
-*.raw filter=lfs diff=lfs merge=lfs -text
-# Audio files - compressed
-*.aac filter=lfs diff=lfs merge=lfs -text
-*.flac filter=lfs diff=lfs merge=lfs -text
-*.mp3 filter=lfs diff=lfs merge=lfs -text
-*.ogg filter=lfs diff=lfs merge=lfs -text
-*.wav filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.train.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.test.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.train.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.test.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.validation.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.test.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.validation.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.validation.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.train.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.train.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.test.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.validation.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.validation00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.validation00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.train02.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.test01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.validation00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.test00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.test01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.validation00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.test00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.train00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.test01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.test00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.test02.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.test02.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.train00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.train01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.train01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.test01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.test00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.test03.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.train00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.validation01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.test03.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.validation01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.validation01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/amazon.train02.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.test02.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.train00.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.train01.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/nyt.train02.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.test03.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/new_wiki.test02.jsonl filter=lfs diff=lfs merge=lfs -text
-data/processed/reddit.train01.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,85 +0,0 @@
----
-license: cc-by-4.0
-pretty_name: SubjQA for question generation
-language: en
-multilinguality: monolingual
-size_categories: 10K<n<100K
-source_datasets: subjqa
-task_categories:
-- text-generation
-task_ids:
-- language-modeling
-tags:
-- question-generation
----
-
-# Dataset Card for "lmqg/qg_squadshifts"
-
-## Dataset Description
-- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
-- **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
-- **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
-
-### Dataset Summary
-This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
- ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](https://arxiv.org/abs/2210.03992).
-Modified version of [SQuADShifts](https://modestyachts.github.io/squadshifts-website/index.html) for question generation (QG) task.
-
-### Supported Tasks and Leaderboards
-* `question-generation`: The dataset can be used to train a model for question generation.
-  Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore (see our paper for more in detail).
-
-### Languages
-English (en)
-
-## Dataset Structure
-
-An example of 'train' looks as follows.
-```
-{
-  "question": "has there ever been a legal challange?",
-  "paragraph": "The status of the Armenian Apostolic Church within the Republic of Armenia is defined in the country's constitution. Article 8.1 of the Constitution of Armenia states: "The Republic of Armenia recognizes the exclusive historical mission of the Armenian Apostolic Holy Church as a national church, in the spiritual life, development of the national culture and preservation of the national identity of the people of Armenia." Among others, ethnographer Hranush Kharatyan has questioned the constitutionality of the phrase "national church".",
-  "answer": "Among others, ethnographer Hranush Kharatyan has questioned the constitutionality of the phrase "national church",
-  "sentence": "Article 8.1 of the Constitution of Armenia states: "The Republic of Armenia recognizes the exclusive historical mission of the Armenian Apostolic Holy Church as a national church, in the spiritual life, development of the national culture and preservation of the national identity of the people of Armenia." Among others, ethnographer Hranush Kharatyan has questioned the constitutionality of the phrase "national church",
-  "paragraph_sentence": "The status of the Armenian Apostolic Church within the Republic of Armenia is defined in the country's constitution. <hl> Article 8.1 of the Constitution of Armenia states: "The Republic of Armenia recognizes the exclusive historical mission of the Armenian Apostolic Holy Church as a national church, in the spiritual life, development of the national culture and preservation of the national identity of the people of Armenia." Among others, ethnographer Hranush Kharatyan has questioned the constitutionality of the phrase "national church". <hl>",
-  "paragraph_answer": "The status of the Armenian Apostolic Church within the Republic of Armenia is defined in the country's constitution. Article 8.1 of the Constitution of Armenia states: "The Republic of Armenia recognizes the exclusive historical mission of the Armenian Apostolic Holy Church as a national church, in the spiritual life, development of the national culture and preservation of the national identity of the people of Armenia." <hl> Among others, ethnographer Hranush Kharatyan has questioned the constitutionality of the phrase "national church". <hl>",
-  "sentence_answer": "Article 8.1 of the Constitution of Armenia states: "The Republic of Armenia recognizes the exclusive historical mission of the Armenian Apostolic Holy Church as a national church, in the spiritual life, development of the national culture and preservation of the national identity of the people of Armenia." <hl> Among others, ethnographer Hranush Kharatyan has questioned the constitutionality of the phrase "national church". <hl>"
-}
-```
-The data fields are the same among all splits.
-- `question`: a `string` feature. 
-- `paragraph`: a `string` feature.
-- `answer`: a `string` feature.
-- `sentence`: a `string` feature.
-- `paragraph_answer`: a `string` feature, which is same as the paragraph but the answer is highlighted by a special token `<hl>`.
-- `paragraph_sentence`: a `string` feature, which is same as the paragraph but a sentence containing the answer is highlighted by a special token `<hl>`.
-- `sentence_answer`: a `string` feature, which is same as the sentence but the answer is highlighted by a special token `<hl>`.
-
-Each of `paragraph_answer`, `paragraph_sentence`, and `sentence_answer` feature is assumed to be used to train a question generation model,
-but with different information. The `paragraph_answer` and `sentence_answer` features are for answer-aware question generation and 
-`paragraph_sentence` feature is for sentence-aware question generation.
-
-### Data Splits
-
-|   name      |train  | valid | test |
-|-------------|------:|------:|-----:|
-|default (all)|9209|6283 |18,844|
-| amazon      |3295|1648|4942|
-| new_wiki    |2646|1323|3969|
-| nyt         |3355|1678|5032|
-| reddit      |3268|1634|4901|
-
-## Citation Information
-```
-@inproceedings{ushio-etal-2022-generative,
-    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
-    author = "Ushio, Asahi  and
-        Alva-Manchego, Fernando  and
-        Camacho-Collados, Jose",
-    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
-    month = dec,
-    year = "2022",
-    address = "Abu Dhabi, U.A.E.",
-    publisher = "Association for Computational Linguistics",
-}
-```

all/qg_squadshifts-test.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0cdcd9c3c7fa3f0b45466bfcb7cd6d57c62f3781508fff46c2fb41aa06b3edea
+size 41940007

all/qg_squadshifts-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe0c9e17a098f5fbddc7e3071a54f8885410d42091063440ceffc1f13613c735
+size 28044897

all/qg_squadshifts-validation.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7258efb706fe77c937bb3f66e4e14518c48211a9b11cfecfd7a4b804aa9c853d
+size 14052001

amazon/qg_squadshifts-test.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c5a690627216154fdd0ca4e88c8a00a1f47cb3876f39cd3d6bda14c89aa98b8
+size 10356900

data/processed/amazon.test02.jsonl → amazon/qg_squadshifts-train.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:688fe93275eac829b458eda6d65a07ca419217d2a6e14634e40d3b3510bad4ab
-size 5589251
+oid sha256:955eb892271ce80357bf3d4d8ca1e28e677027f1034b20afde1ba23a8900cb7f
+size 6997323

data/processed/amazon.test03.jsonl → amazon/qg_squadshifts-validation.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3bb44312872ac5e3cab2b592e947a8c1c7e020220c4d8a51b86bd5161f544e3d
-size 1624067
+oid sha256:bad8c921640978c615d4eaa96c86f3de2ec9ba5a62bbb8ebf325cc23a4a4d288
+size 3528700

data/processed/amazon.train00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6052b2e44588d9f4f2cb63f26ca681d22b9aa287eff9635bb0d5f2e4ca97fd9c
-size 5487087

data/processed/amazon.train01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:d2b4735855b4bffe7b881774ef273dec30af1afb234f5129a37f217e73aac244
-size 5597543

data/processed/amazon.train02.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:006d4ec56795e7d5a25174512fa9c91e9e9c914a3c41844fecb84e35543e3308
-size 1108992

data/processed/amazon.validation00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b3360a31c2c131897d677a90b86d94fe841aa56fd4bcc7b116baff1d7c609615
-size 5515387

data/processed/amazon.validation01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:eb963bbbd214eacfd4c3265ee342fe1cdbc860092c27c1ae5a7f110827d98560
-size 555886

data/processed/new_wiki.test00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ce84ac93052be5e9c33e13dfeaee07895ea6eb1555795fdcfba6e7578518f0ea
-size 5809893

data/processed/new_wiki.test01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b6dd7fdac216a6043d0e37d3d93bf3c2dfc216a9ff8090a8d48ddf859e915e98
-size 5839294

data/processed/new_wiki.test02.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:78ce6f3940cd980581780f3e4ec11a93c6289e5717c4127ea1721d7f0cc9e613
-size 3761720

data/processed/new_wiki.train00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:816d89e0c8841f608afd1554006d06d81fc32663b3f143b1e89c6c1f318a4a32
-size 5823889

data/processed/new_wiki.train01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:4cdf7b91b5b4f2f8c79a9af6ffc4a8550d54c67cfe60b52392ad751d4bc15a62
-size 4443721

data/processed/new_wiki.validation00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b2d5774039f9e84712f6f86e5d2bfef090f40d08cbe90ec7972adb671804bc53
-size 5155823

data/processed/nyt.test00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c2ab45020d2ba1cba7f6461f740004f9ce5d4ef858b8d43064f95f1c9cd1b5bf
-size 6061029

data/processed/nyt.test01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7bcda96580be9e05c2805c5112355a19d3cae4edf63f09584ee13e37b1b8db5b
-size 5929689

data/processed/nyt.test02.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7b42e109dbf474d5a6fbf0a04dd8682ae9ca0b6473937c1a000d059f2f3aa9d6
-size 5984215

data/processed/nyt.test03.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:489eb16f16883b9e6392d025b246ae344f58503eddeaf6ec08272111a42751d3
-size 2077154

data/processed/nyt.train00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b0431aed234ef5f774d37cf67125ba45a427afe93d60a3f579351b099132e8d8
-size 5922343

data/processed/nyt.train01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:13dcc8dbf04d4c8d78cf13bfe573ad2a0258ebe0d56613ec039f2bc8e3316cd2
-size 5961389

data/processed/nyt.train02.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:98fa8faee7b5eca5342880daa5c311ebbb670171380711454ebdc34b2138f8a8
-size 1408146

data/processed/nyt.validation00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ced990654eca70ac4c8bcc432c49c277bf59fe83e9d653ab051feae7a0122992
-size 5893287

data/processed/nyt.validation01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:def01e3d241e815fa5c787b2382956b0678882c753bf730548fda6c7df85c61d
-size 709002

data/processed/reddit.test00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:0a3e045f79238744753ae8b178f1e2157edb3f10d998184db5abe4ca0b4f6f02
-size 5558554

data/processed/reddit.test01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f75abba46df0d46842ecbfb6d6e937c26111a55e03fa10d5a49c3373748903b8
-size 5522538

data/processed/reddit.test02.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:29728a021b0c355eb2214dd7a0f8b26df311c46cef8380f279bb90b255e417b9
-size 5654220

data/processed/reddit.test03.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1f4d0ee8d421a2606fb43ee4c632cddf27290c67d011c28f501eb15bc4d60bbc
-size 1453265

data/processed/reddit.train00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e8040b5c311161f4263b82b3eb7b8cf4e9df0711ea2b21b81b844d84eba455a5
-size 5611873

data/processed/reddit.train01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3ac2bec724fc5fbfaa4a98275d47598db19664b631cc1cf40013e7f059dc762c
-size 5561360

data/processed/reddit.train02.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7199f57ffb2246d2c3cf73eac6e084b2f92f0f9f8dff987ec051a366c1e97921
-size 999150

data/processed/reddit.validation00.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5d7d95bc43edec19adf6855a67daf4e42160060962b0eb074c84c3c78e64ae58
-size 5466110

data/processed/reddit.validation01.jsonl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2391b08e38fccc145aaac5aea06c9096aae5c0e2b9510cbc94aa480ffbd989b1
-size 485303

data/processed/amazon.test00.jsonl → new_wiki/qg_squadshifts-test.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5c97c2503ace547b4e41d2cc38a3450b56786d87386fc12d73754229f422e6d1
-size 5546441
+oid sha256:e1ebfc3910d39d52dcebef74eb5bc89914c93e5be852d6f98622fb351a380b83
+size 8621366

data/processed/amazon.test01.jsonl → new_wiki/qg_squadshifts-train.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f9bce76bdd60d9c67065facbe39c85fe4adfe64d9c26af2de69c1883052ca024
-size 5391114
+oid sha256:183f1d0e5b927a7b812a19ae3af7c642b1f0fc5f4e78ec3bd09ebe95191eaf60
+size 5754745

new_wiki/qg_squadshifts-validation.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:601e1c5cb6587259bcbe853cf273640a9e8e29f08b29145f2ca87e0f0ebd2280
+size 2936252

nyt/qg_squadshifts-test.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:296c892f72559487a213c7db31aeebbfe8412504baf6ca3a1a3adefc133a3074
+size 12091778

nyt/qg_squadshifts-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2ac83daa9c7fc2bf14b9cdc4da975608781242b2c6c4e45bb2a5ca52133ed8bd
+size 8054251

nyt/qg_squadshifts-validation.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d698fc7556cc9a5abc7259ec39cba288afcd94bbbd1bb23e5cab70a42cccb6e4
+size 4043738

process.py

@@ -1,158 +0,0 @@
-""" Script to process raw SQuADshift file for Question Generation format
-cd data/processed
-gsplit -l 1500 -d --additional-suffix=.jsonl new_wiki.test.jsonl new_wiki.test
-gsplit -l 1500 -d --additional-suffix=.jsonl nyt.test.jsonl nyt.test
-gsplit -l 1500 -d --additional-suffix=.jsonl reddit.test.jsonl reddit.test
-gsplit -l 1500 -d --additional-suffix=.jsonl amazon.test.jsonl amazon.test
-
-gsplit -l 1500 -d --additional-suffix=.jsonl new_wiki.train.jsonl new_wiki.train
-gsplit -l 1500 -d --additional-suffix=.jsonl nyt.train.jsonl nyt.train
-gsplit -l 1500 -d --additional-suffix=.jsonl reddit.train.jsonl reddit.train
-gsplit -l 1500 -d --additional-suffix=.jsonl amazon.train.jsonl amazon.train
-
-gsplit -l 1500 -d --additional-suffix=.jsonl new_wiki.validation.jsonl new_wiki.validation
-gsplit -l 1500 -d --additional-suffix=.jsonl nyt.validation.jsonl nyt.validation
-gsplit -l 1500 -d --additional-suffix=.jsonl reddit.validation.jsonl reddit.validation
-gsplit -l 1500 -d --additional-suffix=.jsonl amazon.validation.jsonl amazon.validation
-
-rm -rf new_wiki.test.jsonl
-rm -rf nyt.test.jsonl
-rm -rf reddit.test.jsonl
-rm -rf amazon.test.jsonl
-
-rm -rf new_wiki.train.jsonl
-rm -rf nyt.train.jsonl
-rm -rf reddit.train.jsonl
-rm -rf amazon.train.jsonl
-
-rm -rf new_wiki.validation.jsonl
-rm -rf nyt.validation.jsonl
-rm -rf reddit.validation.jsonl
-rm -rf amazon.validation.jsonl
-
-"""
-import json
-import os
-import re
-from random import shuffle, seed
-from tqdm import tqdm
-
-import spacy
-from datasets import load_dataset
-
-DATASET_NAME = "squadshifts"
-DATASET_TYPES = ['new_wiki', 'nyt', 'reddit', 'amazon']
-HIGHLIGHT_TOKEN = '<hl>'
-GENERATE_TEST_SPLIT = True
-SPLITTER = spacy.load('en_core_web_sm')
-
-
-def get_sentence(document: str): return [str(sent) for sent in SPLITTER(document).sents]
-
-
-def process_single_data(question: str, paragraph: str, answer: str):
-    """ Convert single raw json data into QG format """
-    example = {'question': question, 'paragraph': paragraph, 'answer': answer}
-    start = example['paragraph'].find(example['answer'])
-    end = start + len(answer)
-    assert paragraph[start:end] == answer
-    # get sentence
-    before_tmp = get_sentence(example['paragraph'][:start])
-    if len(before_tmp) == 0:
-        before = ''
-        before_sentence = ''
-    else:
-        if before_tmp[-1].endswith('.'):
-            before = ' '.join(before_tmp)
-            before_sentence = ''
-        else:
-            before = ' '.join(before_tmp[:-1])
-            before_sentence = before_tmp[-1]
-            before_sentence = before_sentence if before_sentence.endswith(' ') else f'{before_sentence} '
-    after_tmp = get_sentence(example['paragraph'][start + len(example['answer']):])
-    if len(after_tmp) == 0:
-        after = ''
-        after_sentence = ''
-    else:
-        after = ' '.join(after_tmp[1:])
-        after_sentence = after_tmp[0]
-        after_sentence = after_sentence if after_sentence.startswith(' ') else f' {after_sentence}'
-    example['sentence'] = f"{before_sentence}{example['answer']}{after_sentence}"
-
-    # get paragraph_sentence
-    before = '' if before == '' else f'{before} '
-    after = '' if after == '' else f' {after}'
-    source_text = '{0}{1} {2} {1}{3}'.format(before, HIGHLIGHT_TOKEN, example['sentence'], after)
-    example['paragraph_sentence'] = re.sub(r'\s+', ' ', source_text)
-
-    # get paragraph_answer
-    source_text = '{0}{1} {2} {1}{3}'.format(
-        example['paragraph'][:start], HIGHLIGHT_TOKEN, example['answer'],
-        example['paragraph'][start + len(example['answer']):])
-    example['paragraph_answer'] = re.sub(r'\s+', ' ', source_text)
-
-    # get sentence_answer
-    if len(before_tmp) == 0 or before_tmp[-1].endswith('.'):
-        before = ''
-    else:
-        before = before_tmp[-1] if before_tmp[-1].endswith(' ') else f'{before_tmp[-1]} '
-    if len(after_tmp) == 0:
-        after = ''
-    else:
-        after = after_tmp[0] if after_tmp[0].startswith(' ') else f' {after_tmp[0]}'
-    source_text = '{0}{1} {2} {1}{3}'.format(before, HIGHLIGHT_TOKEN, example['answer'], after)
-    example['sentence_answer'] = re.sub(r'\s+', ' ', source_text)
-
-    return example
-
-
-if __name__ == '__main__':
-    output = './data/processed'
-    os.makedirs(output, exist_ok=True)
-    for data_type in DATASET_TYPES:
-        dataset = load_dataset(DATASET_NAME, data_type)
-        _split = 'test'
-        tmp_dataset = dataset[_split]
-        full_data = []
-        for single_data in tqdm(tmp_dataset):
-            question_str = single_data['question']  #.replace("\n", ".").replace('"', "'")
-            paragraph_str = single_data['context']  #.replace("\n", ".").replace('"', "'")
-            answer_str = single_data['answers']['text']
-            if type(answer_str) == list:
-                answer_str = answer_str[0]
-            assert type(answer_str) is str, answer_str
-            assert type(question_str) is str, question_str
-            assert type(paragraph_str) is str, paragraph_str
-            tmp_data = process_single_data(question=question_str, paragraph=paragraph_str, answer=answer_str)
-            tmp_data['paragraph_id'] = single_data['id']
-            full_data.append(tmp_data)
-
-        # split test into train/valid/test
-        test_size = int(len(full_data)/2)
-        train_size = int((len(full_data) - test_size) * 2/3)
-        # train_size = 2500
-        valid_size = len(full_data) - train_size - test_size
-        assert train_size + test_size + valid_size == len(full_data), f"{train_size}, {test_size}, {valid_size}"
-        paragraph_ids = list(set([i['paragraph_id'] for i in full_data]))
-        data_dict = {p: [i for i in full_data if i['paragraph_id'] == p] for p in paragraph_ids}
-        seed(0)
-        shuffle(paragraph_ids)
-        lines_train = []
-        lines_test = []
-        lines_valid = []
-
-        for i in paragraph_ids:
-            if len(lines_test) < test_size:
-                lines_test += data_dict[i]
-            elif len(lines_train) < train_size:
-                lines_train += data_dict[i]
-            else:
-                lines_valid += data_dict[i]
-        print(f'STATS(train/valid/test): {data_type}| {len(lines_train)}/{len(lines_valid)}/{len(lines_test)}')
-        with open(f'{output}/{data_type}.test.jsonl', 'w') as f:
-            f.write('\n'.join([json.dumps(i) for i in lines_test]))
-        with open(f'{output}/{data_type}.train.jsonl', 'w') as f:
-            f.write('\n'.join([json.dumps(i) for i in lines_train]))
-        with open(f'{output}/{data_type}.validation.jsonl', 'w') as f:
-            f.write('\n'.join([json.dumps(i) for i in lines_valid]))
-

qg_squadshifts.py

@@ -1,120 +0,0 @@
-""" python -c "from datasets import load_dataset;load_dataset('.')" """
-import json
-from itertools import chain
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-_VERSION = "5.0.1"
-_CITATION = """
-@inproceedings{ushio-etal-2022-generative,
-    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
-    author = "Ushio, Asahi  and
-        Alva-Manchego, Fernando  and
-        Camacho-Collados, Jose",
-    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
-    month = dec,
-    year = "2022",
-    address = "Abu Dhabi, U.A.E.",
-    publisher = "Association for Computational Linguistics",
-}
-"""
-_DESCRIPTION = """[SQuAD Shifts](https://modestyachts.github.io/squadshifts-website/index.html) dataset for question generation (QG) task."""
-_URL = 'https://huggingface.co/datasets/lmqg/qg_squadshifts/resolve/main/data/processed'
-_FILES = {
-    str(datasets.Split.TEST): {
-            'new_wiki': [f'{_URL}/new_wiki.test{i:02d}.jsonl' for i in range(3)],
-            'nyt': [f'{_URL}/nyt.test{i:02d}.jsonl' for i in range(4)],
-            'reddit': [f'{_URL}/reddit.test{i:02d}.jsonl' for i in range(4)],
-            'amazon': [f'{_URL}/amazon.test{i:02d}.jsonl' for i in range(4)]
-        },
-    str(datasets.Split.TRAIN): {
-            'new_wiki': [f'{_URL}/new_wiki.train{i:02d}.jsonl' for i in range(2)],
-            'nyt': [f'{_URL}/nyt.train{i:02d}.jsonl' for i in range(3)],
-            'reddit': [f'{_URL}/reddit.train{i:02d}.jsonl' for i in range(3)],
-            'amazon': [f'{_URL}/amazon.train{i:02d}.jsonl' for i in range(3)]
-        },
-    str(datasets.Split.VALIDATION): {
-            'new_wiki': [f'{_URL}/new_wiki.validation{i:02d}.jsonl' for i in range(1)],
-            'nyt': [f'{_URL}/nyt.validation{i:02d}.jsonl' for i in range(2)],
-            'reddit': [f'{_URL}/reddit.validation{i:02d}.jsonl' for i in range(2)],
-            'amazon': [f'{_URL}/amazon.validation{i:02d}.jsonl' for i in range(2)]
-        },
-}
-# _FILES = {
-#     str(datasets.Split.TEST): {
-#             'new_wiki': [f'{_URL}/new_wiki.test.jsonl'],
-#             'nyt': [f'{_URL}/nyt.test.jsonl'],
-#             'reddit': [f'{_URL}/reddit.test.jsonl'],
-#             'amazon': [f'{_URL}/amazon.test.jsonl']
-#         },
-#     str(datasets.Split.TRAIN): {
-#             'new_wiki': [f'{_URL}/new_wiki.train.jsonl'],
-#             'nyt': [f'{_URL}/nyt.train.jsonl'],
-#             'reddit': [f'{_URL}/reddit.train.jsonl'],
-#             'amazon': [f'{_URL}/amazon.train.jsonl']
-#         },
-#     str(datasets.Split.VALIDATION): {
-#             'new_wiki': [f'{_URL}/new_wiki.validation.jsonl'],
-#             'nyt': [f'{_URL}/nyt.validation.jsonl'],
-#             'reddit': [f'{_URL}/reddit.validation.jsonl'],
-#             'amazon': [f'{_URL}/amazon.validation.jsonl']
-#         },
-# }
-_DOMAIN = list(_FILES[list(_FILES.keys())[0]].keys())
-
-
-class QGSQuADShiftsConfig(datasets.BuilderConfig):
-    """BuilderConfig for SquadQG"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for SquadQG.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(QGSQuADShiftsConfig, self).__init__(**kwargs)
-
-
-class QGSQuADShifts(datasets.GeneratorBasedBuilder):
-
-    BUILDER_CONFIGS = [QGSQuADShiftsConfig(name="all", version=datasets.Version(_VERSION), description="All domain.")]
-    BUILDER_CONFIGS += [QGSQuADShiftsConfig(name=i, version=datasets.Version(_VERSION), description=f"Domain {i}") for i in sorted(_DOMAIN)]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "answer": datasets.Value("string"), "paragraph_question": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "sentence": datasets.Value("string"),
-                    "paragraph": datasets.Value("string"),
-                    "sentence_answer": datasets.Value("string"),
-                    "paragraph_answer": datasets.Value("string"),
-                    "paragraph_sentence": datasets.Value("string"),
-                    "paragraph_id": datasets.Value("string")
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/asahi417/lm-question-generation"
-        )
-
-    def _split_generators(self, dl_manager):
-        if self.config.name == 'all':
-            downloaded_file = dl_manager.download_and_extract({k: list(chain(*list(v.values()))) for k, v in _FILES.items()})
-        else:
-            downloaded_file = dl_manager.download_and_extract({k: v[self.config.name] for k, v in _FILES.items()})
-        return [datasets.SplitGenerator(name=k, gen_kwargs={"filepaths": downloaded_file[k]}) for k in _FILES.keys()]
-
-    def _generate_examples(self, filepaths):
-        _key = 0
-        for filepath in filepaths:
-            logger.info("generating examples from = %s", filepath)
-            with open(filepath, encoding="utf-8") as f:
-                _list = f.read().split('\n')
-                if _list[-1] == '':
-                    _list = _list[:-1]
-                for i in _list:
-                    data = json.loads(i)
-                    yield _key, data
-                    _key += 1
-

reddit/qg_squadshifts-test.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1dd7cd9071fad8899aeb6ff3cc7097d928c31ce1e488f500b290f0ffd3d22e5c
+size 10856496

reddit/qg_squadshifts-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e66473cdb3d4e294cc20e2377bf7dd9282a5e4ef9650399d6807ebf50d5cd0e
+size 7270800

reddit/qg_squadshifts-validation.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c846e09614c7292911a73ad881e56cd55efbde6d716232a7f7e30770e3c53cf5
+size 3560752