mse_dataset_count.py

import jsonlines

# import ollama

#ollama run Hudson/llemma:7b
#deepeval set-ollama Hudson/llemma:7b

if __name__=="__main__":
    question_count = 0
    answer_count = 0
    avg_a_per_q = 0.0

    with jsonlines.open("mse_text_img_QA_dataset.jsonl", mode='r') as reader:
        count = 0
        for row in reader:
            question_count += 1
            for i in range(len(row["answers"])):
                answer_count += 1

    avg_a_per_q = (answer_count * 1.0) / question_count

    print("MSE Dataset:")
    print("Number of Questions = ", question_count)
    print("Number of Answers = ", answer_count)
    print("Average number of Answers per Question = ", avg_a_per_q)