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	console logging example
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				|  | @ -377,6 +377,37 @@ using one of the built-in loggers listed here, you can also | |||
| 
 | ||||
| Writes the results of a training step to the console in a tabular format. | ||||
| 
 | ||||
| <Accordion title="Example console output"> | ||||
| 
 | ||||
| ``` | ||||
| $ 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 | ||||
|   1      200           3.08      18968.78     34.00     0.34 | ||||
|   1      400          31.81      22539.06     33.64     0.34 | ||||
|   1      600          92.13      22794.91     43.80     0.44 | ||||
|   1      800         183.62      21541.39     56.05     0.56 | ||||
|   1     1000         352.49      25461.82     65.15     0.65 | ||||
|   1     1200         422.87      23708.82     71.84     0.72 | ||||
|   1     1400         601.92      24994.79     76.57     0.77 | ||||
|   1     1600         662.57      22268.02     80.20     0.80 | ||||
|   1     1800        1101.50      28413.77     82.56     0.83 | ||||
|   1     2000        1253.43      28736.36     85.00     0.85 | ||||
|   1     2200        1411.02      28237.53     87.42     0.87 | ||||
|   1     2400        1605.35      28439.95     88.70     0.89 | ||||
| ``` | ||||
| 
 | ||||
| Note that the cumulative loss keeps increasing within one epoch, but should | ||||
| start decreasing across epochs. | ||||
| 
 | ||||
|  </Accordion> | ||||
| 
 | ||||
| #### spacy.WandbLogger.v1 {#WandbLogger tag="registered function"} | ||||
| 
 | ||||
| > #### Installation | ||||
|  |  | |||
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