Rename early_stopping_iter to n_early_stopping
@@ -35,7 +35,12 @@ from .. import about
pipeline=("Comma-separated names of pipeline components", "option", "p", str),
vectors=("Model to load vectors from", "option", "v", str),
n_iter=("Number of iterations", "option", "n", int),
- early_stopping_iter=("Maximum number of training epochs without dev accuracy improvement", "option", "e", int),
+ n_early_stopping=(
+ "Maximum number of training epochs without dev accuracy improvement",
+ "option",
+ "ne",
+ int,
+ ),
n_examples=("Number of examples", "option", "ns", int),
use_gpu=("Use GPU", "option", "g", int),
version=("Model version", "option", "V", str),
@@ -75,7 +80,7 @@ def train(
pipeline="tagger,parser,ner",
vectors=None,
n_iter=30,
- early_stopping_iter=None,
+ n_early_stopping=None,
n_examples=0,
use_gpu=-1,
version="0.0.0",
@@ -335,15 +340,15 @@ def train(
gpu_wps=gpu_wps,
)
msg.row(progress, **row_settings)
- if early_stopping_iter is not None:
# Early stopping
+ if n_early_stopping is not None:
current_score = _score_for_model(meta)
if current_score < best_score:
iter_since_best += 1
else:
iter_since_best = 0
best_score = current_score
- if iter_since_best >= early_stopping_iter:
+ if iter_since_best >= n_early_stopping:
msg.text(
"Early stopping, best iteration "
"is: {}".format(i - iter_since_best)
