File size: 1,474 Bytes
e51460b 4d9ded8 f80caad e51460b 4631d9f 4d9ded8 e1655fd c3414ce b31b335 4d9ded8 c3414ce |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
---
languages: fr
task_ids:
- multi-class-classification
- topic-classification
- summarization
task_categories:
- text-classification
- conditional-text-generation
size_categories: 10K<n<100K
---
**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
``` |