Tabular learner
Get a 'Learner' using 'dls', with 'metrics', including a 'TabularModel' created using the remaining params.
tabular_learner( dls, layers = NULL, emb_szs = NULL, config = NULL, n_out = NULL, y_range = NULL, loss_func = NULL, opt_func = Adam(), lr = 0.001, splitter = trainable_params(), cbs = NULL, metrics = NULL, path = NULL, model_dir = "models", wd = NULL, wd_bn_bias = FALSE, train_bn = TRUE, moms = list(0.95, 0.85, 0.95) )
dls |
It is a DataLoaders object. |
layers |
layers |
emb_szs |
emb_szs |
config |
config |
n_out |
n_out |
y_range |
y_range |
loss_func |
It can be any loss function you like. |
opt_func |
It will be used to create an optimizer when Learner.fit is called. |
lr |
It is learning rate. |
splitter |
It is a function that takes self.model and returns a list of parameter groups (or just one parameter group if there are no different parameter groups) |
cbs |
It is one or a list of Callbacks to pass to the Learner. |
metrics |
It is an optional list of metrics, that can be either functions or Metrics. |
path |
İt is used to save and/or load models.Often path will be inferred from dls, but you can override it or pass a Path object to model_dir. Make sure you can write in path/model_dir! |
model_dir |
İt is used to save and/or load models.Often path will be inferred from dls, but you can override it or pass a Path object to model_dir. Make sure you can write in path/model_dir! |
wd |
It is the default weight decay used when training the model. |
wd_bn_bias |
It controls if weight decay is applied to BatchNorm layers and bias. |
train_bn |
It controls if BatchNorm layers are trained even when they are supposed to be frozen according to the splitter. |
moms |
The default momentums used in Learner.fit_one_cycle. |
learner object
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