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README.md
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@@ -21,7 +21,6 @@ Landing Page for the App: https://sites.google.com/view/cs670-finetuning-languag
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App Demonstration Video:
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## Summary
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**milestone3:**
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The following notebook has the tuned model.
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milestone3 notebook: https://github.com/aye-thuzar/CS670Project/blob/main/CS670_milestone_3_AyeThuzar.ipynb
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Please see Milestone4Documentation.md:
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Here is the landing page for my app:
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**************
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App Demonstration Video:
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## Summary
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**milestone3:**
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The following notebook has the tuned model. There are 6 classes in the Harvard USPTO patent dataset and I decided to encode them as follow:
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decision_to_str = {'REJECTED': 0, 'ACCEPTED': 1, 'PENDING': 1, 'CONT-REJECTED': 0, 'CONT-ACCEPTED': 1, 'CONT-PENDING': 1}
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so that I can get a patentability score between 0 and 1.
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I use the pertained-model 'distilbert-base-uncased' from the Hugging face hub and tune it with the smaller dataset.
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The average accuracy of the validation set is about 89%.
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milestone3 notebook: https://github.com/aye-thuzar/CS670Project/blob/main/CS670_milestone_3_AyeThuzar.ipynb
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Please see Milestone4Documentation.md:
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Here is the landing page for my app: https://sites.google.com/view/cs670-finetuning-language-mode/home
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