1021 add flexable attr control
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@ -2,8 +2,8 @@ defaults:
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# - nn_params: nb8_embSum_NMT
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# - nn_params: remi8
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# - nn_params: nb8_embSum_diff_t2m_150M_finetunning
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# - nn_params: nb8_embSum_diff_t2m_600M_pretrainingv2
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- nn_params: nb8_embSum_diff_t2m_600M_finetunningv2
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- nn_params: nb8_embSum_diff_t2m_600M_pretrainingv2
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# - nn_params: nb8_embSum_diff_t2m_600M_finetunningv2
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# - nn_params: nb8_embSum_subPararell
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# - nn_params: nb8_embSum_diff_t2m_150M
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@ -15,7 +15,7 @@ defaults:
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# - nn_params: remi8_main12_head_16_dim512
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# - nn_params: nb5_embSum_diff_main12head16dim768_sub3
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dataset: FinetuneDataset # Pop1k7, Pop909, SOD, LakhClean,PretrainingDataset FinetuneDataset
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dataset: msmidi # Pop1k7, Pop909, SOD, LakhClean,PretrainingDataset FinetuneDataset
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captions_path: dataset/midicaps/train_set.json
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# dataset: SymphonyNet_Dataset # Pop1k7, Pop909, SOD, LakhClean
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@ -44,7 +44,7 @@ train_params:
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focal_gamma: 0
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# learning rate scheduler: 'cosinelr', 'cosineannealingwarmuprestarts', 'not-using', please check train_utils.py for more details
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scheduler : cosinelr
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initial_lr: 0.0004
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initial_lr: 0.0003
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decay_step_rate: 0.8 # means it will reach its lowest point at decay_step_rate * total_num_iter
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num_steps_per_cycle: 20000 # number of steps per cycle for 'cosineannealingwarmuprestarts'
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warmup_steps: 2000 #number of warmup steps
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@ -59,7 +59,7 @@ inference_params:
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data_params:
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first_pred_feature: pitch # compound shifting for NB only, choose the target sub-token (remi and cp are not influenced by this argument)
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split_ratio: 0.998 # train-validation-test split ratio
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aug_type: pitch # random, null | pitch and chord augmentation type
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aug_type: null # random, null | pitch and chord augmentation type
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general:
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debug: False
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make_log: True # True, False | update the log file in wandb online to your designated project and entity
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