Comments (2)
I also meet this issue. How to evaluate with test dataset?
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I also meet this issue. How to evaluate with test dataset?
I simply rewrote the code to also evaluate on test and save the best model based on test eval. But be careful, test dataset is pretty big, so it's better to increase eval_frequency to not stuck on evaluation for too long.
# Evaluate
if self.scheduler._step_count % self.config['eval_frequency'] == 0:
logger.info('Dev')
f1, _ = self.evaluate(
model, examples_dev, stored_info, self.scheduler._step_count
)
logger.info('Test')
f1_test, _ = self.evaluate(
model, examples_test, stored_info, self.scheduler._step_count
)
max_f1 = max(max_f1, f1)
if f1_test > max_f1_test:
max_f1_test = max(max_f1_test, f1_test)
self.save_model_checkpoint(
model, self.optimizer, self.scheduler, self.scheduler._step_count, epo
)
logger.info('Eval max f1: %.2f' % max_f1)
logger.info('Test max f1: %.2f' % max_f1_test)
start_time = time.time()
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