[QEff. finetune_experimnetal] cherry picking PR-787, 791#872
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smedhe wants to merge 3 commits intoquic:ft_experimental_v1from
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[QEff. finetune_experimnetal] cherry picking PR-787, 791#872smedhe wants to merge 3 commits intoquic:ft_experimental_v1from
smedhe wants to merge 3 commits intoquic:ft_experimental_v1from
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Added code for generating PR report. --------- Signed-off-by: Rishin Raj <rishinr@qti.qualcomm.com>
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…t file (quic#787) 1) Adding text field required by TRL's scripts. 2) Passing config_name in the load_dataset_builder 3) Updated test_dataset accordingly. Signed-off-by: Swati Allabadi <sallabad@qti.qualcomm.com> Author: Swati Allabadi <sallabad@qti.qualcomm.com>
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….py) and related code (quic#791) 1) Added FinetuningPipeline (finetune_experiemental.py) which integrates all the components added for HF-trainer and enable running fine tuning through it. 2) Added files to handle PEFT and training config. 3) Made changes in the config_manager and callbacks files. 4) Added unit tests for the FinetuningPipeline (test_finetune.py) 5) Updated tests in test_callback and test_config_manager based on above changes. Finetuning on openai/gsm8k for 5 epochs on single SOC gave the following numbers: {"eval_loss":1.0224987268447876,"eval_runtime":484.8933,"eval_samples_per_second":2.72,"eval_steps_per_second":2.72,"eval_entropy":0.9871161538059735,"eval_num_tokens":6525025.0,"eval_mean_token_accuracy":0.7452040632806826,"epoch":5.0,"num_input_tokens_seen":6525025,"global_step":37365} {"train_runtime":32856.1501,"train_samples_per_second":1.137,"train_steps_per_second":1.137,"total_flos":3.8132170931712e+16,"train_loss":1.0178058738101043,"epoch":5.0,"num_input_tokens_seen":6525025,"global_step":37365} Training loss at the start of training :1.5146, Signed-off-by: Swati Allabadi <sallabad@qti.qualcomm.com> Signed-off-by: Sharvari Medhe <smedhe@qti.qualcomm.com> Author: Swati Allabadi <sallabad@qti.qualcomm.com>
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we are only cherry-picking pr 787 and 791, skipping PR 692,747,785