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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)

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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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This model's model-index metadata is invalid: Schema validation error. "model-index[0].results[0].dataset.type" with value "Reaction to News Stories" fails to match the required pattern: /^(?:[\w-]+\/)?[\w-.]+$/