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PraroopChanda/CLIP-SogCLR-CyCLIP-Hyperparameter-Tuning-for-Small-Batches

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DL-Final Project -636

Team Details:

  • Ishaan Singh Rawal
  • Praroop Chanda For any assistance in running the code, please contact: - [email protected] [email protected] README:
  • To perform hyperparameter tuning using Ray Tune, execute the job files located in the Ray_Tune_Hyperparameter folder. The files are named in the following format:

MyJobRaytune_{Model_Name}_{Optimizer}.sh

  • To Train and validate the code on best tuned hyperparameters, execute job files located in best_job_runs folder. The files are named in the following format:

MyJob{Model_Name}bestlr{Optimizer}.sh

  • To evaluate/Test the code, execute job files located in Eval_Job_Runs folder. The files are named in the following format:

EvalJob_{Model_Name}_{Optimizer}.sh

HereÕs how to use them:

  1. Replace {Model_Name} with the desired model name.
  2. Replace {Optimizer} with the optimizer of your choice.

*** The Training code is available in the Clip1.py file present inside in the iSogCLR>bimodal_exps folder. *** The code used for hyper-parameter tuning is raytune_eval_search.py present inside iSogCLR>bimodal_exps folder. *** The clip_train folder contains the json files for training and validation sets.

Link to Pickle file - https://drive.google.com/file/d/1PRy0jNMSTYXJRBwl47RXU-5ijjZoRV1L/view?usp=sharing

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