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+ ---
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+ license: mit
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+ language:
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+ - en
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+ metrics:
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+ - f1
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+ - accuracy
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+ base_model:
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+ - google-t5/t5-base
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+ library_name: transformers
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+ ---
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+ The official trained models for "Computational Analysis of Communicative Acts for Understanding Crisis News Comment Discourses". The model is based on T5-base, and we used the [Compacter](https://arxiv.org/abs/2106.04647) model and fine-tuned it on our crisis narratives dataset.
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+ To use the model, you need the original code of our paper from the following link:
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+ [Access the Code](https://github.com/Aalto-CRAI-CIS/Acts-in-crisis-narratives/tree/main/few_shot_learning/AdapterModel)
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+ Follow the guidelines, and in the execution script (`adapter.sh`), make the following changes to load this fine-tuned model:
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+ 1. Add your test task method to `seq2seq/data/task.py`, similar to other task methods.
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+ 2. Modify `adapter_inference.sh` with your test task information and run it.
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