162 add a tqdm global progress bar to nas search task #163
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Comment temporarily disable time-consuming workflows. Comment out BERT based text classification workflow possibly permanently, as this is obsolete.
Add branch to workflow.
Added a baseline fine tuning of the full GPT2 to compare against Cerebros text classifier.
Forgot to add dropout.
Amendments to Cerebros model.
Reduce seq length to accelerate job completion.
Up timeout to 300 min.
Correct history indexing error.
Temporary test to fast forward to cerebros model.
Comment out an artifact of GPT test so we this can lint and run.
Fix errors from trying to work too fast ...
Re-corrected the metrics BinaryAccuracy to correct AI introduced error.
Correct metric to rank by (binary accuracy) ...
Uncomment out GPT test ...
Upped number of trials to 5.
Make seq len 750, fix typo.
Try 1024 seq len.
Added branch to the workflow...
Added a positional embedding and a LayerNorm to the text embedding.
Missed position embedding in copy and paste ...
Synchronize embedding dim across embeddings.
Corrected import of PositionEmbedding.
Remove layernorm, concat instead of add.
Try addition to merge embeddings without LayerNorm
Restore optimal run with position embedding. Reduce max levels to fit the optimal run and reduce overhead. Test this to see if it works. if successful, add back the commented out comparison and PR. Then open an issue to optimize the params around this new model. We may need to run this on Katib to optimize the hyperparameters, as the model is fundamentally different than the original and can probably be optimized considerably.
Hard set levels to the known optimum.
Corrected hard set on levels to correct optima.
Restore the best model yet.
Add back the CICD test for image CLS. Prepare for PR.
Comment out workflows that we don't need in dev. Delete permanantly disused workflows
Made AdamW the default optimizer. We need to parameterize this and an optional hyperparameter for the weight_decay.
Test with default params with AdamW.
Combined best hyperparams from the hyperparameter optimization study with AdamW optimizer.
Add branch to workflow to make it start.
Add back all to be used workflows.
Added back the GPT baseline model for comparison.
Optimize NPL workflow for time's sake.
Added tqdm 4.67.1 to requirements.
Try adding a global progress bar.
Added branch to the workflow.
Syntax correction.
Added import statement ...
Try to deal with progress bar floating away.
Fix increment of iter_trial.
Use self.trial_number as the basis for trial in tqdm.
F string with no arguments replaced with regular string.
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Added a global progress bar to the training job. The progress bar is not great (tqdm is not able to see the printouts from the nested logic), but it it is making it easier to trace logs.