31 lines
1.3 KiB
Python
31 lines
1.3 KiB
Python
from flair.models import SequenceTagger
|
|
from flair.datasets import ColumnCorpus
|
|
# from funcs import read_file_by_address
|
|
|
|
def do_evaluate(model_path):
|
|
tagger = SequenceTagger.load(model_path)
|
|
|
|
# تعیین ستونهای داده و بارگذاری مجموعه دادههای آزمایشی
|
|
columns = {0: 'text', 1: 'ner'}
|
|
data_folder = "./data/" # محل ذخیره دادهها
|
|
corpus = ColumnCorpus(data_folder, columns, test_file='test_ds_new.txt') # فایل دادههای آزمایشی
|
|
|
|
result = tagger.evaluate(corpus.test, gold_label_type='ner', mini_batch_size=8)
|
|
|
|
|
|
result_text = f'''##### EVALUATION RESULT #####
|
|
F1 Score: {result.main_score}
|
|
************************************************
|
|
Detailed Results: {result.detailed_results}
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n'''
|
|
return result_text
|
|
|
|
if __name__ == '__main__':
|
|
model_folder = "2025-07-22--15-52-58--HooshvareLab--bert-fa-base-uncased-ner-peyma"
|
|
model_path = f"./taggers/{model_folder}/final-model.pt"
|
|
result = do_evaluate(model_path)
|
|
# print(result)
|
|
with open(f'./taggers/{model_folder}/test-result.txt', 'a+', encoding='utf-8') as file:
|
|
file.write(result)
|