Add readme

README.md

@@ -0,0 +1,53 @@
+
+# UnifiedQA-Reddit-SYAC  
+
+This is an abstractive title answering (TA) / clickbait spoiling model.  
+This is a variant of [allenai/unifiedqa-t5-large](https://huggingface.co/allenai/unifiedqa-t5-large), fine-tuned on the Reddit SYAC dataset.  
+The model was trained as part of my masters thesis:
+
+_Abstractive title answering for clickbait content_  
+
+
+### Disinformation  
+This model has the proven capability of generating, and hallucinating false information.  
+Any use of a TA system such as this one should be with knowledge of this risk.
+
+
+## Performance  
+
+### Intrinsic  
+
+The following scores is the result of intrinsic evaluation on the Reddit SYAC test set.  
+We used a max input length of 2048 and truncated the tokens exceeding this limit.  
+
+| rouge1    | rouge2    | rougeL    | bleu      | meteor   |
+|:----------|:----------|:----------|:----------|:---------|
+| **44.58** | **23.89** | **43.45** | 17.46     | 36.22    |
+
+
+### Qualtiy  
+Using human evaluation, we measured model performance by asking the evaluators to rate the models
+on a scale from 1 to 5 on how good their generated answer was for a given clickbait article.  
+
+Mean quality = 4.065  
+
+### Factuality  
+We included a factuality assessment to address the issue of generating false information.  
+Human raters were asked to place each output in the categories "True", "Irrelevant", and "False".  
+
+| True    | Irrelevant | False    |
+|:-------:|:----------:|:--------:|
+|   85%   |    7.5%    | 7.5%     |
+
+## Cite  
+
+If you use this model, please cite my master's thesis
+
+```
+@mastersthesis{heiervang2022AbstractiveTA
+  title={Abstractive title answering for clickbait content},
+  author={Markus Sverdvik Heiervang},
+  publisher={University of Oslo, Department of Informatics},
+  year={2022}
+}
+```