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@@ -22,22 +22,16 @@ should probably proofread and complete it, then remove this comment. -->
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  # t5-base-DreamBank-Generation-Act-Char
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- This model is a fine-tuned version of [DReAMy-lib/t5-base-DreamBank-Generation-NER-Char](https://huggingface.co/DReAMy-lib/t5-base-DreamBank-Generation-NER-Char) on the None dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.3058
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- - Rouge1: 0.4708
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- - Rouge2: 0.4040
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- - Rougel: 0.4576
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- - Rougelsum: 0.4572
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  ## Model description
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- ## Training procedure
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-
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  The model is trained end-to-end using a text2text solution to annotate dream reports following the Activity feature
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  from the Hall and Van de Castle scoring framework. Given a report, the model generates texts of the form
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  `[(initialiser : activity type : receiver)]`. For those cases where `initialiser` and `receiver` are the same
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- entity, the output will follow the `[(initialiser : alone : none)]` setting.
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  ## Training procedure
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  # t5-base-DreamBank-Generation-Act-Char
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+ This model is a fine-tuned version of [DReAMy-lib/t5-base-DreamBank-Generation-NER-Char](https://huggingface.co/DReAMy-lib/t5-base-DreamBank-Generation-NER-Char) on the DreamBank dataset.
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+ The uploaded model contains the weights of the best-performing model (see table below), tune to annotate a given
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+ dream report according to [Hall and Van de Castle the Activity feature](https://dreams.ucsc.edu/Coding/activities.html)
 
 
 
 
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  ## Model description
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  The model is trained end-to-end using a text2text solution to annotate dream reports following the Activity feature
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  from the Hall and Van de Castle scoring framework. Given a report, the model generates texts of the form
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  `[(initialiser : activity type : receiver)]`. For those cases where `initialiser` and `receiver` are the same
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+ entity, the output will follow the `[(initialiser : alone activity type : none)]` setting.
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  ## Training procedure
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