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.gitattributes

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-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
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-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
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-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md

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----
-license: cc-by-sa-3.0
----
-# CsFEVER experimental Fact-Checking dataset
-
-Czech dataset for fact verification localized from the data points of [FEVER](https://arxiv.org/abs/1803.05355) using the localization scheme described in the [CTKFacts: Czech Datasets for Fact Verification](https://arxiv.org/abs/2201.11115) paper which is currently being revised for publication in LREV journal.
-
-The version you are looking at was reformatted to *Claim*-*Evidence* string pairs for the specific task of NLI - a more general Document-Retrieval-ready interpretation of our datapoints which can be used for training and evaluating the DR models over the June 2016 wikipedia snapshot can be found in the [data_dr]() folder in the JSON Lines format.
-
-## Data Statement
-
-### Curation Rationale
-
-TODO

csfever.py

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-import os
-import pathlib
-from typing import overload
-import datasets
-import json
-
-from datasets.info import DatasetInfo
-
-_VERSION = "0.0.1"
-
-_URL= "data/"
-
-_URLS = {
-    "train": _URL + "train.jsonl",
-    "validation": _URL + "validation.jsonl",
-    "test": _URL + "test.jsonl"
-}
-
-_DESCRIPTION = """\
-CsFEVER is a Czech localisation of the English FEVER datgaset.
-"""
-
-_CITATION = """\
-@article{DBLP:journals/corr/abs-2201-11115,
-  author    = {Jan Drchal and
-               Herbert Ullrich and
-               Martin R{\'{y}}par and
-               Hana Vincourov{\'{a}} and
-               V{\'{a}}clav Moravec},
-  title     = {CsFEVER and CTKFacts: Czech Datasets for Fact Verification},
-  journal   = {CoRR},
-  volume    = {abs/2201.11115},
-  year      = {2022},
-  url       = {https://arxiv.org/abs/2201.11115},
-  eprinttype = {arXiv},
-  eprint    = {2201.11115},
-  timestamp = {Tue, 01 Feb 2022 14:59:01 +0100},
-  biburl    = {https://dblp.org/rec/journals/corr/abs-2201-11115.bib},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
-}
-"""
-
-datasets.utils.version.Version
-class CsFever(datasets.GeneratorBasedBuilder):
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("int32"),
-                    "label": datasets.ClassLabel(names=["REFUTES", "NOT ENOUGH INFO", "SUPPORTS"]),
-                    # datasets.features.Sequence({"text": datasets.Value("string"),"answer_start": datasets.Value("int32"),})
-                    "evidence": datasets.Value("string"),
-                    "claim": datasets.Value("string"),
-                }
-            ),
-            # No default supervised_keys (as we have to pass both question
-            # and context as input).
-            supervised_keys=None,
-            version=_VERSION,
-            homepage="https://fcheck.fel.cvut.cz/dataset/",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-
-        return [
-            datasets.SplitGenerator(datasets.Split.TRAIN, {
-                "filepath": downloaded_files["train"]
-            }),
-            datasets.SplitGenerator(datasets.Split.VALIDATION, {
-                "filepath": downloaded_files["validation"]
-            }),
-            datasets.SplitGenerator(datasets.Split.TEST, {
-                "filepath": downloaded_files["test"]
-            }),
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        key = 0
-        with open(filepath, encoding="utf-8") as f:
-            for line in f:
-                datapoint = json.loads(line)
-                yield key, {
-                    "id": datapoint["id"],
-                    "evidence": " ".join(datapoint["evidence"]),
-                    "claim": datapoint["claim"],
-                    "label": datapoint["label"]
-                }
-                key += 1

data/train.jsonl

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-size 168449812

data/test.jsonl → default/csfever-test.parquet

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-size 15499684
+oid sha256:9445a670642ffbe574f0665c6b4a95f23ea6d376fe257db9468b94b8eeb71158
+size 7884012

data/validation.jsonl → default/csfever-train.parquet

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+oid sha256:029744fae866fc803f8158e75cab0fe5003e9843cee9f8645bc8eb6740590eb5
+size 85614680

data_dr/train_deepl.jsonl → default/csfever-validation.parquet

@@ -1,3 +1,3 @@
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+size 8048591

experiments.ipynb

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-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# 🤗 Experiments over hf dataset"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import datasets\n",
-    "from datasets import load_dataset"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Using custom data configuration default\n",
-      "Reusing dataset ctkfacts_nli (/Users/bertik/.cache/huggingface/datasets/ctkfacts_nli/default/0.0.0/5dcd805dfbd9694ead18f5cf4da8d902a1a1ca53685a5ebabd33f3d314dd597d)\n",
-      "100%|██████████| 3/3 [00:00<00:00, 409.28it/s]\n"
-     ]
-    }
-   ],
-   "source": [
-    "d=load_dataset(\"csfever.py\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "DatasetDict({\n",
-       "    train: Dataset({\n",
-       "        features: ['id', 'label', 'evidence', 'claim'],\n",
-       "        num_rows: 2903\n",
-       "    })\n",
-       "    validation: Dataset({\n",
-       "        features: ['id', 'label', 'evidence', 'claim'],\n",
-       "        num_rows: 377\n",
-       "    })\n",
-       "    test: Dataset({\n",
-       "        features: ['id', 'label', 'evidence', 'claim'],\n",
-       "        num_rows: 431\n",
-       "    })\n",
-       "})"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "d"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "        _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n",
-      "        _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n",
-      "        _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n",
-      "        _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n",
-      "        _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n",
-      "\n",
-      "        \n",
-      "Username: ^C\n",
-      "Traceback (most recent call last):\n",
-      "  File \"/opt/homebrew/bin/huggingface-cli\", line 8, in <module>\n",
-      "    sys.exit(main())\n",
-      "  File \"/opt/homebrew/lib/python3.9/site-packages/huggingface_hub/commands/huggingface_cli.py\", line 41, in main\n",
-      "    service.run()\n",
-      "  File \"/opt/homebrew/lib/python3.9/site-packages/huggingface_hub/commands/user.py\", line 169, in run\n",
-      "    username = input(\"Username: \")\n",
-      "KeyboardInterrupt\n"
-     ]
-    }
-   ],
-   "source": [
-    "!huggingface-cli login"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Downloading: 100%|██████████| 2.55k/2.55k [00:00<00:00, 1.33MB/s]\n",
-      "Using custom data configuration default\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Downloading and preparing dataset ctkfacts_nli/default to /Users/bertik/.cache/huggingface/datasets/heruberuto___ctkfacts_nli/default/0.0.0/5dcd805dfbd9694ead18f5cf4da8d902a1a1ca53685a5ebabd33f3d314dd597d...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Downloading: 100%|██████████| 2.14M/2.14M [00:00<00:00, 2.86MB/s]\n",
-      "Downloading: 100%|██████████| 247k/247k [00:00<00:00, 386kB/s]\n",
-      "Downloading: 100%|██████████| 287k/287k [00:00<00:00, 450kB/s]\n",
-      "100%|██████████| 3/3 [00:04<00:00,  1.66s/it]\n",
-      "100%|██████████| 3/3 [00:00<00:00, 976.56it/s]\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Dataset ctkfacts_nli downloaded and prepared to /Users/bertik/.cache/huggingface/datasets/heruberuto___ctkfacts_nli/default/0.0.0/5dcd805dfbd9694ead18f5cf4da8d902a1a1ca53685a5ebabd33f3d314dd597d. Subsequent calls will reuse this data.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|██████████| 3/3 [00:00<00:00, 811.96it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "DatasetDict({\n",
-       "    train: Dataset({\n",
-       "        features: ['id', 'label', 'evidence', 'claim'],\n",
-       "        num_rows: 2903\n",
-       "    })\n",
-       "    validation: Dataset({\n",
-       "        features: ['id', 'label', 'evidence', 'claim'],\n",
-       "        num_rows: 377\n",
-       "    })\n",
-       "    test: Dataset({\n",
-       "        features: ['id', 'label', 'evidence', 'claim'],\n",
-       "        num_rows: 431\n",
-       "    })\n",
-       "})"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "load_dataset(\"heruberuto/ctkfacts_nli\", use_auth_token=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "interpreter": {
-   "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
-  },
-  "kernelspec": {
-   "display_name": "Python 3.9.7 64-bit",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.7"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

test.py

@@ -1,3 +0,0 @@
-import datasets
-
-datasets.load_dataset("csfever.py")