generated_from_trainer

This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the Webis-Clickbait-17 dataset. It achieves the following results on the evaluation set:

Loss: 0.0261

The following list presents the current performances achieved by the participants. As primary evaluation measure, Mean Squared Error (MSE) with respect to the mean judgments of the annotators is used. Our result is 0,0261 for the MSE metric. We do not compute the other metrics. We try not to cheat using unknown data at the time of the challenge. We do not use k-fold cross validation techniques.

team MSE F1 Precision Recall Accuracy Runtime
goldfish 0.024 0.741 0.739 0.742 0.876 16:20:21
caush 0.026 00:11:00
monkfish 0.026 0.694 0.785 0.622 0.870 03:41:35
dartfish 0.027 0.706 0.733 0.681 0.865 00:47:07
torpedo19 0.03 0.677 0.755 0.614 0.861 00:52:44
albacore 0.031 0.67 0.731 0.62 0.855 00:01:10
blobfish 0.032 0.646 0.738 0.574 0.85 00:03:22
zingel 0.033 0.683 0.719 0.65 0.856 00:03:27
anchovy 0.034 0.68 0.717 0.645 0.855 00:07:20
ray 0.034 0.684 0.691 0.677 0.851 00:29:28
icarfish 0.035 0.621 0.768 0.522 0.849 01:02:57
emperor 0.036 0.641 0.714 0.581 0.845 00:04:03
carpetshark 0.036 0.638 0.728 0.568 0.847 00:08:05
electriceel 0.038 0.588 0.727 0.493 0.835 01:04:54
arowana 0.039 0.656 0.659 0.654 0.837 00:35:24
pineapplefish 0.041 0.631 0.642 0.621 0.827 00:54:28
whitebait 0.043 0.565 0.7 0.474 0.826 00:04:31