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