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Ines Montani 2019-07-10 10:27:29 +02:00
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website/docs/usage/training.md
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@ -630,13 +630,13 @@ should be somewhat larger, especially if your documents are long.
### Learning rate, regularization and gradient clipping {#tips-hyperparams}
By default spaCy uses the Adam solver, with default settings (`learn_rate=0.001`,
`beta1=0.9`, `beta2=0.999`). Some researchers have said they found
these settings terrible on their problems – but they've always performed very
well in training spaCy's models, in combination with the rest of our recipe. You
can change these settings directly, by modifying the corresponding attributes on
the `optimizer` object. You can also set environment variables, to adjust the
defaults.
By default spaCy uses the Adam solver, with default settings
(`learn_rate=0.001`, `beta1=0.9`, `beta2=0.999`). Some researchers have said
they found these settings terrible on their problems – but they've always
performed very well in training spaCy's models, in combination with the rest of
our recipe. You can change these settings directly, by modifying the
corresponding attributes on the `optimizer` object. You can also set environment
variables, to adjust the defaults.
There are two other key hyper-parameters of the solver: `L2` **regularization**,
and **gradient clipping** (`max_grad_norm`). Gradient clipping is a hack that's