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I wanted to provide you with the commit logs for my project on Google Colab, as there was an oversight in updating the Git repository. The attached files contain the details of the commits made during the recent project updates. Thank you for your understanding, and I apologize for any inconvenience this may have caused.
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i didn't get any feedback till now |
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Hi Ritika, this PR was created quite late (last week), even though I can see commits were on time. Tutor will look at this ASAP, but there may be penalties for late PR submission. |
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This is an initial inspection, no action is required at this point Difficulty: Hard Readme:
Commit messages:
Code:
Functionality/Performance:
General comments:
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MarkingCommits on time but late PR -4 Good Practice (Design/Commenting, TF/Torch Usage)Adequate design and implementation, only as a notebook -2 Recognition ProblemSolves problem, but has training/validation loss irregularities -1 Commit LogMeaningful commit messages sometimes -1 DocumentationReadMe acceptable/good, no usage -1 Pull RequestSuccessful Pull Request (Working Algorithm Delivered on Time in InCorrect Branch) -2 |
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Feedback marks possible +2 if the requested changes are made (see above). |
creating files as described in the feedback
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Have some feedback attempts but was unsuccessful. So no feedback marks granted. |
creating files as described in the feedback
creating files as described in the feedback
creating files as described in the feedback
Pull Request: ADNI_Brain_Visual_Transformer_47306725 Readme
Summary:
This pull request aims to enhance the README documentation for the "ADNI_Brain_Visual_Transformer_47306725" project. The improvements include providing a more structured overview of the project, clarifying the Vision Transformer architecture, detailing the dataset, and addressing the challenges faced during model training. Additionally, the pull request incorporates suggestions for improving clarity and readability.
Additional Details:
The revised README is organized into clear sections, such as "Overview," "Vision Transformers," "Setting Parameters," "Build and Train the Model," and "Conclusion."
Detailed explanations have been added to sections like "Architecture of Vision Transformer," providing insights into the alterations made to the original Vision Transformer and how the model functions.
The "Training and Testing Process" section has been expanded to provide a comprehensive understanding of the experimentation process with different hyperparameters and the observed results from multiple models.
Suggestions for potential enhancements, such as considering a larger dataset or leveraging pre-trained models, have been included in the "Conclusion" section to guide future improvements.
Name: Ritika Rana
Student ID: 47306725