From 3929431af1991d76f3594f89c8dda2c87ee8d5e6 Mon Sep 17 00:00:00 2001 From: Ines Montani Date: Mon, 31 Aug 2020 17:06:33 +0200 Subject: [PATCH] Update docs [ci skip] --- website/docs/api/top-level.md | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md index b747007b0..d437ecc07 100644 --- a/website/docs/api/top-level.md +++ b/website/docs/api/top-level.md @@ -357,8 +357,8 @@ are returned: one for logging the information for each training step, and a second function that is called to finalize the logging when the training is finished. To log each training step, a [dictionary](/usage/training#custom-logging) is passed on from the -[training script](/api/cli#train), including information such as the training -loss and the accuracy scores on the development set. +[`spacy train`](/api/cli#train), including information such as the training loss +and the accuracy scores on the development set. There are two built-in logging functions: a logger printing results to the console in tabular format (which is the default), and one that also sends the @@ -366,6 +366,8 @@ results to a [Weights & Biases](https://www.wandb.com/) dashboard. Instead of using one of the built-in loggers listed here, you can also [implement your own](/usage/training#custom-logging). +#### spacy.ConsoleLogger.v1 {#ConsoleLogger tag="registered function"} + > #### Example config > > ```ini @@ -373,19 +375,21 @@ using one of the built-in loggers listed here, you can also > @loggers = "spacy.ConsoleLogger.v1" > ``` -#### spacy.ConsoleLogger.v1 {#ConsoleLogger tag="registered function"} - Writes the results of a training step to the console in a tabular format. - + + +```cli +$ python -m spacy train config.cfg +``` ``` -$ python -m spacy train config.cfg ℹ Using CPU ℹ Loading config and nlp from: config.cfg ℹ Pipeline: ['tok2vec', 'tagger'] ℹ Start training ℹ Training. Initial learn rate: 0.0 + E # LOSS TOK2VEC LOSS TAGGER TAG_ACC SCORE --- ------ ------------ ----------- ------- ------ 1 0 0.00 86.20 0.22 0.00