Update parquet files

.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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-*.joblib filter=lfs diff=lfs merge=lfs -text
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-*.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
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-validation_data.csv filter=lfs diff=lfs merge=lfs -text

train_data.csv → Summarization Part Data/summarization_optimization-train.parquet

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 version https://git-lfs.github.com/spec/v1
-oid sha256:63aa4cabc7c14d9c42586f06b12b095beb3469ab2bd7154abd97d3f6bf09d9e2
-size 178145961
+oid sha256:470db01da13bab3c917bca061f057a2c1b34aa857641f81b80294b8df18c1887
+size 105965117

validation_data.csv → Summarization Part Data/summarization_optimization-validation.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b8f3ebe76e1f6f25406a0c951bede30fe1ce738ad83a239b2a08256cba54a964
-size 44623623
+oid sha256:f7dadde2c99d2f5b82f8b3345392e9988317602ae415b3d8c3b6b1f6989f51f4
+size 26535081

summarization_optimization.py

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-import json
-import pandas as pd
-import datasets
-import csv
-from datasets.tasks import Summarization
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_DESCRIPTION = """\
-Aihub Document summarization data
-"""
-_URL = "https://huggingface.co/datasets/metamong1/summarization_optimization/resolve/main/"
-_URLS = {
-    "train_data": _URL + "train_data.csv",
-    "validation_data": _URL + "validation_data.csv",
-}
-
-class SummarizationOptimization(datasets.GeneratorBasedBuilder):
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="Summarization Part Data",
-            version=datasets.Version("1.0.0", ""),
-            description="Text Summarization & Generation Title for optimization",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "doc_id": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "doc_type": datasets.Value("string"),
-                    "file": datasets.Value("string"),
-                }
-            ),
-            # No default supervised_keys (as we have to pass both question
-            # and context as input).
-            supervised_keys=None,
-            homepage="https://huggingface.co/datasets/metamong1/summarization_optimization",
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train_data"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation_data"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        with open(filepath, newline='', encoding="utf-8") as csvfile:
-            reader = csv.reader(csvfile, delimiter=",")
-            feature_name = next(reader)
-
-            idx = 0
-            for row in reader:
-                features = {
-                    "doc_id" : row[1],
-                    "title" : row[2],
-                    "text" : row[3],
-                    "doc_type" : row[4],
-                    "file" : row[5],
-                }
-                
-                yield idx, features
-                idx += 1