The scores after every 30 epochs doesn't change at all during fine-tuning

[tanayshah23]

Hi,

I am trying to fine-tune the t03b model with a 4-shot approach on the heart dataset. On checking the logs after every 30 epochs, I don't see any difference in the scores that are printed.
It prints the same score after the first 30 epochs and the same at the end of 5600 epochs

{"AUC": 0.5823586744639375, "PR": 0.6555849741948994, "micro_f1": 0.5706521739130435, "macro_f1": 0.4795001253267447, "accuracy": 0.5706521739130435, "num": 184, "num_steps": -1, "score_gt": 0.3382242697736491, "score_cand": 0.37344987593267276}
....
....
....
{"AUC": 0.5823586744639375, "PR": 0.6555849741948994, "micro_f1": 0.5706521739130435, "macro_f1": 0.4795001253267447, "accuracy": 0.5706521739130435, "num": 184, "num_steps": 30, "score_gt": 0.3382242697736491, "score_cand": 0.37344987593267276}

I also tried the same thing on a different dataset and got the same results. Here's the screenshot:

Can you please tell me what am I doing wrong?

[stefanhgm]

Hello @tanayshah23 ,

as explained in the issue #16, we treat the test data as validation set in the code, since we don't do parameter tuning. Your output shows the validation performance after every 30th epoch, hence, the test performance after evert 30th epoch. I suspect that based on 4 examples the model is not learning anything anymore after the 30th epoch so that the test performance does not change.

I hope that helps!