# Creates embeddings for the sentences in the test_text list. 
# The np.array() function is used to convert the result into a numpy array.
# The .tolist() function is used to convert the numpy array into a list, which might be easier to work with.
vectors = np.array(tuned_model.predict(test_text)).tolist()

# Calls the plot_similarity function to create a similarity plot.
plot_similarity(test_text, vectors, 90, "tuned model")

# Computes STS benchmark score for the tuned model
pearsonr = sts_benchmark(tuned_model)
print("STS Benachmark: " + str(pearsonr))