SOULAMA/QA-text-generation-alpaca-data-cleaned
Dataset Card for mBART-QA-Processed This dataset consists of tokenized pairs of instructions and contexts designed for fine-tuning Sequence-to-Sequence models (like mBART or T5) on Question Answering tasks. Dataset Details Dataset Description The dataset is a processed version of a Question Answering corpus (SQuAD-like). It has been formatted to follow a specific prompt structure: instruction: {question} input: {context}. The targets (labels) are… See the full description on the dataset page: https://huggingface.co/datasets/SOULAMA/QA-text-generation-alpaca-data-cleaned.
Dataset Card for mBART-QA-Processed
This dataset consists of tokenized pairs of instructions and contexts designed for fine-tuning Sequence-to-Sequence models (like mBART or T5) on Question Answering tasks.
Dataset Details
Dataset Description
The dataset is a processed version of a Question Answering corpus (SQuAD-like). It has been formatted to follow a specific prompt structure: instruction: {question} input: {context}. The targets (labels) are the direct text answers.
- Curated by: SOULAMA H.Ismael
- Language(s) (NLP): English (
en) - License: Apache-2.0
Dataset Sources
- Repository: SOULAMA/google-mbart-large-50-QA-text-generation
Uses
Direct Use
This dataset is intended for fine-tuning generative models to perform document-based question answering. It is optimized for text2text-generation tasks where the model must generate a concise answer based on a provided snippet.
Out-of-Scope Use
The dataset should not be used for open-domain QA without providing a context, as it is designed for grounded generation. It is not suitable for training models in languages other than English without further augmentation.
Dataset Structure
The dataset contains three main features:
- input_ids: Token