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Update 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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  ************************
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  ## Summary
@@ -47,7 +46,15 @@ Dataset: https://github.com/suzgunmirac/hupd
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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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@@ -55,7 +62,7 @@ milestone3 notebook: https://github.com/aye-thuzar/CS670Project/blob/main/CS670_
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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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  ************************
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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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  **************