Use softmax pooler output in train_textcat
@@ -42,7 +42,8 @@ def main(
nlp = spacy.load(model)
print(f"Loaded model '{model}'")
- textcat = nlp.create_pipe("pytt_textcat", config={"exclusive_classes": True})
+ textcat = nlp.create_pipe("pytt_textcat",
+ config={"architecture": "softmax_pooler_output"})
# add label to text classifier
textcat.add_label("POSITIVE")
textcat.add_label("NEGATIVE")
