fasttext_supervised_text_classification_train_predict_evaluate.py

1import fasttext
2
3# 1. Train a supervised classification model
4# Note: 'data.train' should be a text file where each line is:
5# __label__<label_name> <text_content>
6model = fasttext.train_supervised(input="data.train")
7
8# 2. Save the trained model for later use
9model.save_model("model_filename.bin")
10
11# 3. Predict the label of a specific text
12# Returns: (('__label__example',), array([0.99]))
13prediction = model.predict("Which financial institution do you recommend?")
14print(prediction)
15
16# 4. Evaluate the model on a test set
17# Returns: (number of samples, precision, recall)
18result = model.test("data.test")
19print(f"Samples: {result[0]}, Precision: {result[1]}, Recall: {result[2]}")