From 4b82c485de187896a38c441587b7bd4d04f2821e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Louf?= Date: Tue, 10 Dec 2019 14:49:53 +0100 Subject: [PATCH] remove misplaced summarization documentation --- examples/README.md | 30 ------------------------------ 1 file changed, 30 deletions(-) diff --git a/examples/README.md b/examples/README.md index 620304ea77..b6b3908810 100644 --- a/examples/README.md +++ b/examples/README.md @@ -24,8 +24,6 @@ pip install -r ./examples/requirements.txt | [Multiple Choice](#multiple-choice) | Examples running BERT/XLNet/RoBERTa on the SWAG/RACE/ARC tasks. | [Named Entity Recognition](#named-entity-recognition) | Using BERT for Named Entity Recognition (NER) on the CoNLL 2003 dataset, examples with distributed training. | | [XNLI](#xnli) | Examples running BERT/XLM on the XNLI benchmark. | -| [Abstractive summarization](#abstractive-summarization) | Using the BertAbs -model finetuned on the CNN/DailyMail dataset to generate summaries. | ## TensorFlow 2.0 Bert models on GLUE @@ -646,34 +644,6 @@ micro avg 0.8722 0.8774 0.8748 13869 macro avg 0.8712 0.8774 0.8740 13869 ``` -## Abstractive summarization - -Based on the script -[`run_summarization_finetuning.py`](https://github.com/huggingface/transformers/blob/master/examples/run_summarization_finetuning.py). - -Before running this script you should download **both** CNN and Daily Mail -datasets from [Kyunghyun Cho's website](https://cs.nyu.edu/~kcho/DMQA/) (the -links next to "Stories") in the same folder. Then uncompress the archives by running: - -```bash -tar -xvf cnn_stories.tgz && tar -xvf dailymail_stories.tgz -``` - -note that the finetuning script **will not work** if you do not download both -datasets. We will refer as `$DATA_PATH` the path to where you uncompressed both -archive. - -```bash -export DATA_PATH=/path/to/dataset/ - -python run_summarization_finetuning.py \ - --output_dir=output \ - --model_type=bert2bert \ - --model_name_or_path=bert2bert \ - --do_train \ - --data_path=$DATA_PATH \ -``` - ## XNLI Based on the script [`run_xnli.py`](https://github.com/huggingface/transformers/blob/master/examples/run_xnli.py).