Roberta base finetuned on a dataset of empathic reactions to news stories (Buechel et al., 2018; Tafreshi et al., 2021, 2022) Table of Contents Model Details How to Get Started With the Model Uses Risks, Limitations and Biases Training Model Details Model Description: This model is a fine tuned checkpoint of RoBERTA base, fine tuned for Track 1 of theWASSA 2022 Shared Task predicting empathy and distress scores on a dataset of reactions to news stories. This model attained an average Pearson's correlation (r) of 0.416854 on the dev set (for comparison, the top team had an average r of .54 on the test set ). Training Training Data An extended version of the empathic reactions to news stories dataset Fine tuning hyper parameters learning rate = 1e 5 batch size = 32 warmup = 600 max seq length = 128 num train epochs = 3.0
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