Datasets:
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README.md
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This is a dataset created for training Russian-language Seq2Seq and CLM models primarily for tasks related to Closed-Domain QA.
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The dataset includes 3 main tasks
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1. AAQG (Answer-Aware Question Answering) - generation of questions based on context, provided the answer is known
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2. QG - generating questions based on context, without a known answer
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3. QA - the standard task of answering a question based on context.
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4. Instuct - an additional task for following instructions, intended as an auxiliary task for the model to better follow different instructions, but this is not its main task.
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AAQG, QG, QA tasks are generated based on regular datasets for which the context, question and correct answer are known. They are generated in a ratio of 0.
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List of datasets used to compile this dataset:
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1. sberquad
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2. russian_super_glue/muserc
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3. russian_super_glue/danetqa
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4. 1/5 of SiberiaSoft/SiberianInstructions-small - for instructions
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Prompts used for QA tasks:
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```python
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AAQG_PROMPT = "
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QG_PROMPT = "
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QA_PROMPT = "
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```
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### Authors
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This is a dataset created for training Russian-language Seq2Seq and CLM models primarily for tasks related to Closed-Domain QA.
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+
The dataset includes 3 main tasks:
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1. AAQG (Answer-Aware Question Answering) - generation of questions based on context, provided the answer is known
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2. QG - generating questions based on context, without a known answer
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3. QA - the standard task of answering a question based on context.
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AAQG, QG, QA tasks are generated based on regular datasets for which the context, question and correct answer are known. They are generated in a ratio of 0.4, 0.3 and 0.3, respectively.
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List of datasets used to compile this dataset:
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1. sberquad
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2. russian_super_glue/muserc
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3. russian_super_glue/danetqa
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Prompts used for QA tasks:
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```python
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AAQG_PROMPT = """AAQG | Текст: '{context}'. Ответ: '{answer}'"""
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QG_PROMPT = """QG | Текст: '{context}'"""
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QA_PROMPT = """QA | Текст: '{context}'. Вопрос: '{question}'"""
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```
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### Authors
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