from sklearn.datasets import load_wine
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import f1_score
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(
data.data, data.target, test_size=0.4, random_state=1234
clf = RandomForestClassifier(**params)
clf.fit(X_train, y_train)
y_train_pred = clf.predict_proba(X_train)
y_test_pred = clf.predict_proba(X_test)
train_f1 = f1_score(y_train, y_train_pred.argmax(axis=1), average="macro")
test_f1 = f1_score(y_test, y_test_pred.argmax(axis=1), average="macro")
print(f"Train f1:{train_f1} | Test f1:{test_f1}")