predictia
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convswin2sr_mediterranean

super-resolution

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pereza commited on Oct 30, 2023

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b6e575f

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1 Parent(s): 4bc6cac

Update README.md

adding training time

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@@ -100,12 +100,6 @@ Significant research has explored bias and fairness issues with language models
 and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes
 across protected classes; identity characteristics; and sensitive, social, and occupational groups.
 # Training Details
 ## Training Data
@@ -159,7 +153,8 @@ The interpolation transformed the CERRA dataset to match the regular grid struct
 ### Speeds, Sizes, Times
-- Training time:
 - Model size: The ConvSwin2SR model is a robust machine learning model boasting a total of 12,383,377 parameters.
   This size reflects a substantial capacity for learning and generalizing complex relationships within the data, enabling the model to

 and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes
 across protected classes; identity characteristics; and sensitive, social, and occupational groups.
 # Training Details
 ## Training Data
 ### Speeds, Sizes, Times
+- Training time: The training duration for the ConvSwin2SR model is notably extensive, clocking in at 3,648 days to complete a total of 100 epochs with
+- a batch size of 2 for a total number of batches equal to ~43000.
 - Model size: The ConvSwin2SR model is a robust machine learning model boasting a total of 12,383,377 parameters.
   This size reflects a substantial capacity for learning and generalizing complex relationships within the data, enabling the model to