* Update bart example docs
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@@ -1,4 +1,4 @@
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### Get the CNN/Daily Mail Data
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### Get the CNN Data
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To be able to reproduce the authors' results on the CNN/Daily Mail dataset you first need to 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:
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```bash
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@@ -32,6 +32,7 @@ unzip stanford-corenlp-full-2018-10-05.zip
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cd stanford-corenlp-full-2018-10-05
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export CLASSPATH=stanford-corenlp-3.9.2.jar:stanford-corenlp-3.9.2-models.jar
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```
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Then run `ptb_tokenize` on `test.target` and your generated hypotheses.
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### Rouge Setup
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Install `files2rouge` following the instructions at [here](https://github.com/pltrdy/files2rouge).
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I also needed to run `sudo apt-get install libxml-parser-perl`
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@@ -27,9 +27,11 @@ def generate_summaries(lns, out_file, batch_size=8, device=DEFAULT_DEVICE):
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attention_mask=dct["attention_mask"].to(device),
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num_beams=4,
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length_penalty=2.0,
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max_length=140,
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min_length=55,
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max_length=142, # +2 from original because we start at step=1 and stop before max_length
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min_length=56, # +1 from original because we start at step=1
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no_repeat_ngram_size=3,
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early_stopping=True,
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do_sample=False,
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)
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dec = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summaries]
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for hypothesis in dec:
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