Use fewer iterations by default to avoid overfitting on blank model (resolves
@@ -73,7 +73,7 @@ TRAIN_DATA = [
new_model_name=("New model name for model meta.", "option", "nm", str),
output_dir=("Optional output directory", "option", "o", Path),
n_iter=("Number of training iterations", "option", "n", int))
-def main(model=None, new_model_name='animal', output_dir=None, n_iter=50):
+def main(model=None, new_model_name='animal', output_dir=None, n_iter=20):
"""Set up the pipeline and entity recognizer, and train the new entity."""
if model is not None:
nlp = spacy.load(model) # load existing spaCy model
