mpuels
ee4d6fdd40
Fix typo in comment
2017-12-09 13:14:57 +01:00
ines
726fb2d0b5
Use fewer iterations by default to avoid overfitting on blank model ( resolves #1632 )
2017-11-23 15:27:12 +01:00
ines
ec08996000
Add note on tags matching tokenization (see #1613 )
2017-11-20 15:12:47 +01:00
ines
f36fab39b0
Don't rename component in intent parser example ( resolves #1551 )
...
Otherwise, the default saved model won't know that it's supposed to create spaCy's 'parser'.
2017-11-10 23:35:38 +01:00
Ines Montani
1a23a0f87e
Remove broken link ( resolves #1541 )
2017-11-10 12:28:39 +01:00
ines
89bd40b821
Fix print statement in textcat training example ( resolves #1515 )
2017-11-08 17:17:40 +01:00
ines
a09c096d3c
Get docs ready for v2.0.0
2017-11-07 12:00:43 +01:00
ines
173b1551af
Update examples
2017-11-07 01:22:30 +01:00
ines
1b1c9105b4
Update example compatibility statements
2017-11-07 01:11:45 +01:00
ines
8fb48b9b91
Update and document new util functions
2017-11-07 00:22:43 +01:00
Matthew Honnibal
d7016d4050
Update intent parser example
2017-11-06 23:31:11 +01:00
ines
fe498b3d5e
Update training examples to use "simple style"
2017-11-06 23:14:04 +01:00
ines
2dca9e71a1
Add notes on catastrophic forgetting (see #1496 )
2017-11-06 13:17:02 +01:00
Matthew Honnibal
e033162a1d
Update tagger training example
2017-11-01 21:49:08 +01:00
ines
8f1d3fc3ee
Update textcat example
2017-11-01 17:09:22 +01:00
Matthew Honnibal
dad8f09fba
Fix print statements in text classifier example
2017-11-01 16:34:31 +01:00
ines
bfe17b7df1
Fix begin_training if get_gold_tuples is None
2017-11-01 13:14:31 +01:00
ines
4b196fdf7f
Fix formatting
2017-11-01 00:43:22 +01:00
ines
33af6ac69a
Use even smaller examle size
...
100 was still too much, so try 20 instead
2017-10-30 19:46:45 +01:00
ines
f02b0af821
Fix path and use smaller example size
...
500 was too larger and caused laggy rendering
2017-10-30 19:44:35 +01:00
ines
18dde7869a
Update training data docs and add vocab JSONL
2017-10-30 19:40:05 +01:00
ines
b5643d8575
Update intent parser docs and add to usage docs
2017-10-27 04:49:05 +02:00
ines
9dfca0f2f8
Add example for custom intent parser
2017-10-27 03:55:11 +02:00
ines
4d272e25ee
Fix examples
2017-10-27 03:55:04 +02:00
ines
a7b9074b4c
Update textcat training example and docs
2017-10-27 00:48:45 +02:00
ines
b61866a2e4
Update textcat example
2017-10-27 00:32:19 +02:00
ines
f81cc0bd1c
Fix usage of disable_pipes
2017-10-27 00:31:30 +02:00
ines
f57043e6fe
Update docstring
2017-10-26 16:29:08 +02:00
ines
b90e958975
Update tagger and parser examples and add to docs
2017-10-26 16:27:42 +02:00
ines
f1529463a8
Update tagger training example
2017-10-26 16:19:02 +02:00
ines
e44bbb5361
Remove old example
2017-10-26 16:12:41 +02:00
ines
421c3837e8
Fix formatting
2017-10-26 16:11:25 +02:00
ines
4d896171ae
Use plac annotations for arguments
2017-10-26 16:11:20 +02:00
ines
c3b681e5fb
Use plac annotations for arguments and add n_iter
2017-10-26 16:11:05 +02:00
ines
bc2c92f22d
Use plac annotations for arguments
2017-10-26 16:10:56 +02:00
ines
b5c74dbb34
Update parser training example
2017-10-26 15:15:37 +02:00
ines
586b9047fd
Use create_pipe instead of importing the entity recognizer
2017-10-26 15:15:26 +02:00
ines
d425ede7e9
Fix example
2017-10-26 15:15:08 +02:00
ines
9d58673aaf
Update train_ner example for spaCy v2.0
2017-10-26 14:24:12 +02:00
ines
e904075f35
Remove stray print statements
2017-10-26 14:24:00 +02:00
ines
c30258c3a2
Remove old example
2017-10-26 14:23:52 +02:00
ines
615c315d70
Update train_new_entity_type example to use disable_pipes
2017-10-25 14:56:53 +02:00
ines
2b8e7c45e0
Use better training data JSON example
2017-10-24 16:00:56 +02:00
ines
9bf5751064
Pretty-print JSON
2017-10-24 12:22:17 +02:00
ines
6675755005
Add training data JSON example
2017-10-24 12:05:10 +02:00
Jeroen Bobbeldijk
84c6c20d1c
Fix #1444 : fix pipeline logic and wrong paramater in update call
2017-10-22 15:18:36 +02:00
Jeffrey Gerard
5ba970b495
minor cleanup
2017-10-12 12:34:46 -07:00
Jeffrey Gerard
39d3cbfdba
Bugfix example script train_ner_standalone.py, fails after training
2017-10-12 11:39:12 -07:00
Matthew Honnibal
563f46f026
Fix multi-label support for text classification
...
The TextCategorizer class is supposed to support multi-label
text classification, and allow training data to contain missing
values.
For this to work, the gradient of the loss should be 0 when labels
are missing. Instead, there was no way to actually denote "missing"
in the GoldParse class, and so the TextCategorizer class treated
the label set within gold.cats as complete.
To fix this, we change GoldParse.cats to be a dict instead of a list.
The GoldParse.cats dict should map to floats, with 1. denoting
'present' and 0. denoting 'absent'. Gradients are zeroed for categories
absent from the gold.cats dict. A nice bonus is that you can also set
values between 0 and 1 for partial membership. You can also set numeric
values, if you're using a text classification model that uses an
appropriate loss function.
Unfortunately this is a breaking change; although the functionality
was only recently introduced and hasn't been properly documented
yet. I've updated the example script accordingly.
2017-10-05 18:43:02 -05:00
Matthew Honnibal
f1b86dff8c
Update textcat example
2017-10-04 15:12:28 +02:00