MiniLM evidence types This model is a fine tuned version of microsoft/MiniLM L12 H384 uncased on the evidence types dataset. It achieved the following results on the evaluation set: Loss: 1.8672 Macro f1: 0.3726 Weighted f1: 0.7030 Accuracy: 0.7161 Balanced accuracy: 0.3616 Training and evaluation data The data set, as well as the code that was used to fine tune this model can be found in the GitHub repository BA Thesis Information Science Persuasion Strategies Training hyperparameters The following hyperparameters were used during training: learning rate: 2e 05 train batch size: 16 eval batch size: 16 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: linear num epochs: 20 mixed precision training: Native AMP Training results Training Loss Epoch Step Validation Loss Macro f1 Weighted f1 Accuracy Balanced accuracy : : : : : : : : : : : : : : : : 1.4106 1.0 250 1.2698 0.1966 0.6084 0.6735 0.2195 1.1437 2.0 500 1.0985 0.3484 0.6914 0.7116 0.3536 0.9714 3.0 750 1.0901 0.2606 0.6413 0.6446 0.2932 0.8382 4.0 1000 1.0197 0.2764 0.7024 0.7237 0.2783 0.7192 5.0 1250 1.0895 0.2847 0.6824 0.6963 0.2915 0.6249 6.0 1500 1.1296 0.3487 0.6888 0.6948 0.3377 0.533…
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