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Best model after epoch #46
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natuan
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bfineran
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May 21, 2022
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@natuan great feature to have. Looks like it would be tough, but is there any way we can get this change to be just on the sparseml repo? always trying to minimize divergence between our fork and upstream where possible - but given it's a one line change in a long function having it here seems ok.
one idea might be adding in best_model_after_epoch to the sparseml side trainer/scripts and having a conditional check for it in the save function. Thoughts?
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I think we could move this into sparseml by overloading |
bfineran
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May 27, 2022
anmarques
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bfineran
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May 27, 2022
KSGulin
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Oct 14, 2022
Disable FP16 on QAT start (#12) * Override LRScheduler when using LRModifiers * Disable FP16 on QAT start * keep wrapped scaler object for training after disabling Using QATMatMul in DistilBERT model class (#41) Removed double quantization of output of context layer. (#45) Fix DataParallel validation forward signatures (#47) * Fix: DataParallel validation forward signatures * Update: generalize forward_fn selection Best model after epoch (#46) fix sclaer check for non fp16 mode in trainer (#38) Mobilebert QAT (#55) * Remove duplicate quantization of vocabulary. enable a QATWrapper for non-parameterized matmuls in BERT self attention (#9)
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Oct 18, 2022
* Update trainer and model flows to accommodate sparseml Disable FP16 on QAT start (#12) * Override LRScheduler when using LRModifiers * Disable FP16 on QAT start * keep wrapped scaler object for training after disabling Using QATMatMul in DistilBERT model class (#41) Removed double quantization of output of context layer. (#45) Fix DataParallel validation forward signatures (#47) * Fix: DataParallel validation forward signatures * Update: generalize forward_fn selection Best model after epoch (#46) fix sclaer check for non fp16 mode in trainer (#38) Mobilebert QAT (#55) * Remove duplicate quantization of vocabulary. enable a QATWrapper for non-parameterized matmuls in BERT self attention (#9) * Utils and auxillary changes update Zoo stub loading for SparseZoo 1.1 refactor (#54) add flag to signal NM integration is active (#32) Add recipe_name to file names * Fix errors introduced in manual cherry-pick upgrade Co-authored-by: Benjamin Fineran <[email protected]>
KSGulin
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Jun 19, 2023
* Add recipe_name to default file names * Upgrade to transformers release V4.30.2 (#62) * Update trainer and model flows to accommodate sparseml Disable FP16 on QAT start (#12) * Override LRScheduler when using LRModifiers * Disable FP16 on QAT start * keep wrapped scaler object for training after disabling Using QATMatMul in DistilBERT model class (#41) Removed double quantization of output of context layer. (#45) Fix DataParallel validation forward signatures (#47) * Fix: DataParallel validation forward signatures * Update: generalize forward_fn selection Best model after epoch (#46) fix sclaer check for non fp16 mode in trainer (#38) Mobilebert QAT (#55) * Remove duplicate quantization of vocabulary. enable a QATWrapper for non-parameterized matmuls in BERT self attention (#9) * Utils and auxillary changes update Zoo stub loading for SparseZoo 1.1 refactor (#54) add flag to signal NM integration is active (#32) Add recipe_name to file names * Fix errors introduced in manual cherry-pick upgrade Co-authored-by: Benjamin Fineran <[email protected]> * update build versions for NM fork pypi push (#74) * fix nightly package name (#75) * add make build command (#76) * add GHA workflow files to build nightly and release packages (#77) * add GHA workflow files to build nightly and release packages * fix name --------- Co-authored-by: dhuang <[email protected]> * bump up version to 1.6.0 (#79) Co-authored-by: dhuang <[email protected]> --------- Co-authored-by: Konstantin <[email protected]> Co-authored-by: Konstantin Gulin <[email protected]> Co-authored-by: dhuangnm <[email protected]> Co-authored-by: dhuang <[email protected]>
dsikka
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Aug 17, 2023
* Add recipe_name to default file names * Upgrade to transformers release V4.30.2 (#62) * Update trainer and model flows to accommodate sparseml Disable FP16 on QAT start (#12) * Override LRScheduler when using LRModifiers * Disable FP16 on QAT start * keep wrapped scaler object for training after disabling Using QATMatMul in DistilBERT model class (#41) Removed double quantization of output of context layer. (#45) Fix DataParallel validation forward signatures (#47) * Fix: DataParallel validation forward signatures * Update: generalize forward_fn selection Best model after epoch (#46) fix sclaer check for non fp16 mode in trainer (#38) Mobilebert QAT (#55) * Remove duplicate quantization of vocabulary. enable a QATWrapper for non-parameterized matmuls in BERT self attention (#9) * Utils and auxillary changes update Zoo stub loading for SparseZoo 1.1 refactor (#54) add flag to signal NM integration is active (#32) Add recipe_name to file names * Fix errors introduced in manual cherry-pick upgrade Co-authored-by: Benjamin Fineran <[email protected]> * update build versions for NM fork pypi push (#74) * fix nightly package name (#75) * add make build command (#76) * add GHA workflow files to build nightly and release packages (#77) * add GHA workflow files to build nightly and release packages * fix name --------- Co-authored-by: dhuang <[email protected]> * bump up version to 1.6.0 (#79) Co-authored-by: dhuang <[email protected]> --------- Co-authored-by: Konstantin <[email protected]> Co-authored-by: Konstantin Gulin <[email protected]> Co-authored-by: dhuangnm <[email protected]> Co-authored-by: dhuang <[email protected]>
dsikka
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Aug 17, 2023
* Add recipe_name to default file names * Upgrade to transformers release V4.30.2 (#62) * Update trainer and model flows to accommodate sparseml Disable FP16 on QAT start (#12) * Override LRScheduler when using LRModifiers * Disable FP16 on QAT start * keep wrapped scaler object for training after disabling Using QATMatMul in DistilBERT model class (#41) Removed double quantization of output of context layer. (#45) Fix DataParallel validation forward signatures (#47) * Fix: DataParallel validation forward signatures * Update: generalize forward_fn selection Best model after epoch (#46) fix sclaer check for non fp16 mode in trainer (#38) Mobilebert QAT (#55) * Remove duplicate quantization of vocabulary. enable a QATWrapper for non-parameterized matmuls in BERT self attention (#9) * Utils and auxillary changes update Zoo stub loading for SparseZoo 1.1 refactor (#54) add flag to signal NM integration is active (#32) Add recipe_name to file names * Fix errors introduced in manual cherry-pick upgrade Co-authored-by: Benjamin Fineran <[email protected]> * update build versions for NM fork pypi push (#74) * fix nightly package name (#75) * add make build command (#76) * add GHA workflow files to build nightly and release packages (#77) * add GHA workflow files to build nightly and release packages * fix name --------- Co-authored-by: dhuang <[email protected]> * bump up version to 1.6.0 (#79) Co-authored-by: dhuang <[email protected]> --------- Co-authored-by: Konstantin <[email protected]> Co-authored-by: Konstantin Gulin <[email protected]> Co-authored-by: dhuangnm <[email protected]> Co-authored-by: dhuang <[email protected]>
bfineran
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Oct 26, 2023
* Add recipe_name to default file names * Upgrade to transformers release V4.30.2 (#62) * Update trainer and model flows to accommodate sparseml Disable FP16 on QAT start (#12) * Override LRScheduler when using LRModifiers * Disable FP16 on QAT start * keep wrapped scaler object for training after disabling Using QATMatMul in DistilBERT model class (#41) Removed double quantization of output of context layer. (#45) Fix DataParallel validation forward signatures (#47) * Fix: DataParallel validation forward signatures * Update: generalize forward_fn selection Best model after epoch (#46) fix sclaer check for non fp16 mode in trainer (#38) Mobilebert QAT (#55) * Remove duplicate quantization of vocabulary. enable a QATWrapper for non-parameterized matmuls in BERT self attention (#9) * Utils and auxillary changes update Zoo stub loading for SparseZoo 1.1 refactor (#54) add flag to signal NM integration is active (#32) Add recipe_name to file names * Fix errors introduced in manual cherry-pick upgrade Co-authored-by: Benjamin Fineran <[email protected]> * update build versions for NM fork pypi push (#74) * fix nightly package name (#75) * add make build command (#76) * add GHA workflow files to build nightly and release packages (#77) * add GHA workflow files to build nightly and release packages * fix name --------- Co-authored-by: dhuang <[email protected]> * bump up version to 1.6.0 (#79) Co-authored-by: dhuang <[email protected]> --------- Co-authored-by: Konstantin <[email protected]> Co-authored-by: Konstantin Gulin <[email protected]> Co-authored-by: dhuangnm <[email protected]> Co-authored-by: dhuang <[email protected]>
bfineran
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Oct 27, 2023
(previous commits) * Add recipe_name to default file names * Upgrade to transformers release V4.30.2 (#62) * Update trainer and model flows to accommodate sparseml Disable FP16 on QAT start (#12) * Override LRScheduler when using LRModifiers * Disable FP16 on QAT start * keep wrapped scaler object for training after disabling Using QATMatMul in DistilBERT model class (#41) Removed double quantization of output of context layer. (#45) Fix DataParallel validation forward signatures (#47) * Fix: DataParallel validation forward signatures * Update: generalize forward_fn selection Best model after epoch (#46) fix sclaer check for non fp16 mode in trainer (#38) Mobilebert QAT (#55) * Remove duplicate quantization of vocabulary. enable a QATWrapper for non-parameterized matmuls in BERT self attention (#9) * Utils and auxillary changes update Zoo stub loading for SparseZoo 1.1 refactor (#54) add flag to signal NM integration is active (#32) Add recipe_name to file names * Fix errors introduced in manual cherry-pick upgrade Co-authored-by: Benjamin Fineran <[email protected]> * update build versions for NM fork pypi push (#74) * fix nightly package name (#75) * add make build command (#76) * add GHA workflow files to build nightly and release packages (#77) * add GHA workflow files to build nightly and release packages * fix name --------- Co-authored-by: dhuang <[email protected]> * bump up version to 1.6.0 (#79) Co-authored-by: dhuang <[email protected]> --------- Co-authored-by: Konstantin <[email protected]> Co-authored-by: Konstantin Gulin <[email protected]> Co-authored-by: dhuangnm <[email protected]> Co-authored-by: dhuang <[email protected]> minor improvements for build workflow files (#83) Co-authored-by: dhuang <[email protected]> fix minor issue (#84) Co-authored-by: dhuang <[email protected]> OPT with quantizable MatMuls (#85) fix a minor issue for release build (#86) Co-authored-by: dhuang <[email protected]> update version in version.py Testmo (#91) * improve GHA workflow files to build nightly and release, and report status to testmo * clean up * report exit code * Assign value to exit_code --------- Co-authored-by: dhuang <[email protected]> Update trainer.py - fix DistributedSampler import (#93) DistributedSampler is used but not imported in `trainer.py` Research/llama/bmm quantization (#94) * Quantize attention matmuls * Quantize attention matmuls bump base transformers version
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This change introduces an option to specify an epoch after which the best model could be saved, and it could be used in conjunction with the existing flags "metric_for_best_model" and "load_best_model_at_end". A use case here is that when doing pruning or transferring followed by quantization, one might use this flag to obtain the best quantized model (which is only valid after the pruning/transferring ends).