Sync

.gitignore

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+.venv/
+.ruff_cache/

README.md

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+---
+language:
+- uk
+license:
+- proprietary
+size_categories:
+- 1K<n<100K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- topic-classification
+pretty_name: UA-L Topics Corpus
+dataset_info:
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype:
+      class_label:
+        names:
+            '0': kriminalnie_pravo
+            '1': pidpriemnicka_dialnist
+            '2': spadkove_pravo
+            '3': mizhnarodni_pravovidnosini
+            '4': zhitlovi_pravovidnosini
+            '5': korporativnie_pravo
+            '6': immighratsiia_iemighratsiia
+            '7': prava_spozhivachiv
+            '8': medicina
+            '9': pratsevlashtuvvannya
+            '10': bankivska_diialnist
+            '11': mytne_pravo
+            '12': doghovirni_vidnosini
+            '13': dovircha_vlastnist
+            '14': reklama
+            '15': viiskovie_pravo
+            '16': gospodarskie_pravo
+            '17': notarialni_pytanniia
+            '18': tsivilne_pravo
+            '19': litsienzuvannia
+            '20': ziemielnie_pravo
+            '21': nierukhomist
+            '22': opodatkuvannia
+            '23': sudova_praktika
+            '24': inshe
+            '25': piensiiata_sotsialni_viplati
+            '26': reyestraciya_likvidaciya_bankrutstvo
+            '27': ekologiya
+            '28': administrativnie_pravo
+            '29': gromadianski_pravovidnosini
+            '30': strakhuvannya
+            '31': vighotovliennia_produktsiyi_ta_nadannia_poslugh
+            '32': intieliektualna_vlasnist
+            '33': simejne_pravo
+            '34': dierzhavni_zakupivli
+            '35': prava_vnutrishno_pieriemishchienikh_osib
+            '36': sotsialnyj_zakhist
+            '37': investitsii
+            '38': avtovlasnykam
+  splits:
+  - name: train
+    num_bytes: 2092033
+    num_examples: 3021
+  - name: test
+    num_bytes: 122281
+    num_examples: 159
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train.jsonl
+  - split: test
+    path: data/test.jsonl
+train-eval-index:
+- config: default
+  task: text-classification
+  task_id: multi_class_classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    text: text
+    label: target
+  metrics:
+  - type: accuracy
+    name: Accuracy
+  - type: f1
+    name: F1 macro
+    args:
+      average: macro
+  - type: f1
+    name: F1 micro
+    args:
+      average: micro
+  - type: f1
+    name: F1 weighted
+    args:
+      average: weighted
+  - type: precision
+    name: Precision macro
+    args:
+      average: macro
+  - type: precision
+    name: Precision micro
+    args:
+      average: micro
+  - type: precision
+    name: Precision weighted
+    args:
+      average: weighted
+  - type: recall
+    name: Recall macro
+    args:
+      average: macro
+  - type: recall
+    name: Recall micro
+    args:
+      average: micro
+  - type: recall
+    name: Recall weighted
+    args:
+      average: weighted
+---
+
+# `ual-topics`
+
+## Install
+
+```shell
+uv venv --python 3.12
+
+source .venv/bin/activate
+
+uv pip install -r requirements.txt
+
+# in development mode
+uv pip install -r requirements-dev.txt
+```

data/labels.json

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+{"__label__kriminalnie_pravo": 0, "__label__pidpriemnicka_dialnist": 1, "__label__spadkove_pravo": 2, "__label__mizhnarodni_pravovidnosini": 3, "__label__zhitlovi_pravovidnosini": 4, "__label__korporativnie_pravo": 5, "__label__immighratsiia_iemighratsiia": 6, "__label__prava_spozhivachiv": 7, "__label__medicina": 8, "__label__pratsevlashtuvvannya": 9, "__label__bankivska_diialnist": 10, "__label__mytne_pravo": 11, "__label__doghovirni_vidnosini": 12, "__label__dovircha_vlastnist": 13, "__label__reklama": 14, "__label__viiskovie_pravo": 15, "__label__gospodarskie_pravo": 16, "__label__notarialni_pytanniia": 17, "__label__tsivilne_pravo": 18, "__label__litsienzuvannia": 19, "__label__ziemielnie_pravo": 20, "__label__nierukhomist": 21, "__label__opodatkuvannia": 22, "__label__sudova_praktika": 23, "__label__inshe": 24, "__label__piensiiata_sotsialni_viplati": 25, "__label__reyestraciya_likvidaciya_bankrutstvo": 26, "__label__ekologiya": 27, "__label__administrativnie_pravo": 28, "__label__gromadianski_pravovidnosini": 29, "__label__strakhuvannya": 30, "__label__vighotovliennia_produktsiyi_ta_nadannia_poslugh": 31, "__label__intieliektualna_vlasnist": 32, "__label__simejne_pravo": 33, "__label__dierzhavni_zakupivli": 34, "__label__prava_vnutrishno_pieriemishchienikh_osib": 35, "__label__sotsialnyj_zakhist": 36, "__label__investitsii": 37, "__label__avtovlasnykam": 38}

extract_labels.py

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+import json
+import polars as pl
+
+test = pl.read_ndjson("data/raw_test.jsonl")
+train = pl.read_ndjson("data/raw_train.jsonl")
+
+print(test)
+print(train)
+
+unique_test_labels = test.select("label").unique()
+unique_train_labels = train.select("label").unique()
+
+print("Unique labels in test data:", unique_test_labels)
+print("Unique labels in train data:", unique_train_labels)
+
+unique_concatenated = pl.concat([unique_test_labels, unique_train_labels]).unique()
+
+print("Unique labels in both test and train data:", unique_concatenated)
+
+print(unique_concatenated)
+
+labels = {}
+for idx, value in enumerate(unique_concatenated.rows()):
+    print(idx, value[0])
+
+    labels[value[0]] = idx
+
+print(labels)
+
+with open("data/labels.json", "w") as f:
+    json.dump(labels, f)

generate_datasets.py

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+import json
+import polars as pl
+
+with open("data/labels.json", "r") as f:
+    labels = json.load(f)
+
+print(labels)
+
+test = pl.read_ndjson("data/raw_test.jsonl")
+train = pl.read_ndjson("data/raw_train.jsonl")
+
+print(test)
+print(train)
+
+test_json = []
+for value in test.rows():
+    label, text = value
+
+    print(labels[label], text)
+
+    test_json.append({"label": labels[label], "text": text})
+
+train_json = []
+for value in train.rows():
+    label, text = value
+
+    print(labels[label], text)
+
+    train_json.append({"label": labels[label], "text": text})
+
+with open("data/test.jsonl", "w") as f:
+    f.writelines("\n".join(json.dumps(i) for i in test_json))
+
+with open("data/train.jsonl", "w") as f:
+    f.writelines("\n".join(json.dumps(i) for i in train_json))

requirements-dev.txt

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+ruff

requirements.txt

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+polars