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--- |
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languages: fr |
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task_ids: |
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- multi-class-classification |
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- topic-classification |
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- summarization |
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task_categories: |
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- text-classification |
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- conditional-text-generation |
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size_categories: 10K<n<100K |
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--- |
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**QR-AN Dataset: a classification and generation dataset of french Parliament questions-answers.** |
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This is a dataset for theme/topic classification, made of questions and answers from https://www2.assemblee-nationale.fr/recherche/resultats_questions . \ |
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It contains 188 unbalanced classes, 80k questions-answers divided into 3 splits: train (60k), val (10k) and test (10k). \ |
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Can be used for generation with 'qran_generation' |
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This dataset is compatible with the [`run_summarization.py`](https://github.com/huggingface/transformers/tree/master/examples/pytorch/summarization) script from Transformers if you add this line to the `summarization_name_mapping` variable: |
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```python |
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"ccdv/cass-summarization": ("question", "answer") |
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``` |
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Compatible with [run_glue.py](https://github.com/huggingface/transformers/tree/master/examples/pytorch/text-classification) script: |
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``` |
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export MODEL_NAME=camembert-base |
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export MAX_SEQ_LENGTH=512 |
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python run_glue.py \ |
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--model_name_or_path $MODEL_NAME \ |
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--dataset_name cassandra-themis/QR-AN \ |
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--do_train \ |
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--do_eval \ |
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--max_seq_length $MAX_SEQ_LENGTH \ |
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--per_device_train_batch_size 8 \ |
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--gradient_accumulation_steps 4 \ |
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--learning_rate 2e-5 \ |
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--num_train_epochs 1 \ |
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--max_eval_samples 500 \ |
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--output_dir tmp/QR-AN |
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``` |
