label_ids actually mean from
I trained a multilabel classification model and tested it on a test dataset. The
Trainer.predict.metrics gave me the output below:
label_ids should be the predicted label so I did a confusion matrix between
label_ids and my testing data. The result shows a perfect prediction with accuracy = 1, recall =1, precision = 1 etc.
I realized something was wrong so I computed the label myself with the logit values produced by
compute_labels = tf.round(tf.nn.sigmoid(test_prediction.predictions))
Running confusion matrix with the
compute_labels and the test data, I am able to get a reasonable prediction results that replicated the output of
Trainer.predict.metrics (i.e., above image).
My question is: What does
Trainer.predict.label_ids mean? Why the output I got from this argument produced a perfect prediction results which was obviously wrong?
Thank you in advance