Maria Castellanos
commited on
Commit
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b1db5fd
1
Parent(s):
5c22f32
change submission freq
Browse files
app.py
CHANGED
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@@ -165,7 +165,7 @@ def gradio_interface():
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- In the spirit of open science and open source we would love to see code showing how you created your submission if possible, in the form of a Github Repository.
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If not possible due to IP or other constraints you must at a minimum provide a short report written methodology based on the template [here](https://docs.google.com/document/d/1bttGiBQcLiSXFngmzUdEqVchzPhj-hcYLtYMszaOqP8/edit?usp=sharing).
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**Make sure your lat submission before the deadline includes a link to a report or to a Github repository.**
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- Each participant can submit as many times as they like, up to a limit of
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- The endpoints will be judged individually by mean absolute error (**MAE**), while an overall leaderboard will be judged by the macro-averaged relative absolute error (**MA-RAE**).
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- For endpoints that are not already on a log scale (e.g LogD) they will be transformed to log scale to minimize the impact of outliers on evaluation.
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- We will estimate errors on the metrics using bootstrapping and use the statistical testing workflow outlined in [this paper](https://chemrxiv.org/engage/chemrxiv/article-details/672a91bd7be152b1d01a926b) to determine if model performance is statistically distinct.
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| 165 |
- In the spirit of open science and open source we would love to see code showing how you created your submission if possible, in the form of a Github Repository.
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| 166 |
If not possible due to IP or other constraints you must at a minimum provide a short report written methodology based on the template [here](https://docs.google.com/document/d/1bttGiBQcLiSXFngmzUdEqVchzPhj-hcYLtYMszaOqP8/edit?usp=sharing).
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**Make sure your lat submission before the deadline includes a link to a report or to a Github repository.**
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| 168 |
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- Each participant can submit as many times as they like, up to a limit of once per day. **Only your latest submission will be considered for the final leaderboard.**
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| 169 |
- The endpoints will be judged individually by mean absolute error (**MAE**), while an overall leaderboard will be judged by the macro-averaged relative absolute error (**MA-RAE**).
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| 170 |
- For endpoints that are not already on a log scale (e.g LogD) they will be transformed to log scale to minimize the impact of outliers on evaluation.
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| 171 |
- We will estimate errors on the metrics using bootstrapping and use the statistical testing workflow outlined in [this paper](https://chemrxiv.org/engage/chemrxiv/article-details/672a91bd7be152b1d01a926b) to determine if model performance is statistically distinct.
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