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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
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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