Hi , I can see the potential of this project but it lacks clear documentation. <p

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Missing documentation. about spacy_crfsuite HOT 5 CLOSED

talmago commented on June 9, 2024 1

Missing documentation.

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talmago commented on June 9, 2024 1

@arunnbaba See new release for documentation. You can now use both command line and jupyter notebook to train / eval the CRF model. Hope this helps !

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arunnbaba commented on June 9, 2024

Hi, So can you please elaborate on the process of training the model with Json files

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talmago commented on June 9, 2024

@arunnbaba sure, i'll soon upload further documentation for training, including JSON and MD dataset example. On the meantime, you can take a look at this test which demonstrates the conversion from JSON to MD.

Then, you can use the following command line to train the crf model on your examples;

$ python -m spacy_crfsuite.trainer train train.json --model-dir model/

If you want to override the model hyper params you can use a config file from command line (i.e -c config.json).
Model parameters are described in here. Notice that currently it's not possible to configure CRF params except for the L1_c, L2_c and max_iterations. This should change in the future to allow all possible values for the crfsuite estimator.

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arunnbaba commented on June 9, 2024

Thanks for your reply

…

On Fri, 31 Jul 2020, 1:22 am Tal Almagor, ***@***.***> wrote: @arunnbaba <https://github.com/arunnbaba> sure, i'll soon upload further documentation for training, including JSON and MD dataset example. On the meantime, you can take a look at this test <https://github.com/talmago/spacy_crfsuite/blob/master/tests/test_markdown.py> which demonstrates the conversion from JSON to MD. Then, you can use the following command line to train the crf model on your examples; $ python -m spacy_crfsuite.trainer train train.json --model-dir model/ If you want to override the model hyper params you can use a config file from command line (i.e -c config.json). Model parameters are described in here <https://github.com/talmago/spacy_crfsuite/blob/master/spacy_crfsuite/crf_extractor.py#L32>. Notice that currently it's not possible to configure CRF params except for the L1_c, L2_c and max_iterations. This should change in the future to allow all possible values for the crfsuite estimator <https://github.com/TeamHG-Memex/sklearn-crfsuite/blob/master/sklearn_crfsuite/estimator.py#L22> . — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#1 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADRKCWWH4P4P5CPDZ54G4OTR6HFRNANCNFSM4PL2HBFQ> .

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arunnbaba commented on June 9, 2024

Thank you for your quick actions and it helped me a lot in my work. In the meantime if u have time look into my pandas_ui u might find it useful in u r work.

…

On Sun, 2 Aug 2020, 1:56 am Tal Almagor, ***@***.***> wrote: Closed #1 <#1>. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#1 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADRKCWUFE5QKRTTB4A4DTGTR6R27DANCNFSM4PL2HBFQ> .

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