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My model works fine with adamw_bnb_8bit. When i switched to galore_adamw_8bit with 'all-linear', an exception is raised 'can't optimize a non-leaf'
Seq2SeqTrainingArguments( output_dir = model_name_or_path, save_strategy = 'no', logging_steps = 100, bf16 = True if torch.cuda.is_available() else False, dataloader_pin_memory = True, dataloader_num_workers = 8, num_train_epochs = 1, #1, # 2, do_train=True, learning_rate = learning_rate, # 5e-5, # optim = 'adamw_bnb_8bit', optim="galore_adamw_8bit_layerwise", optim_target_modules='all-linear', lr_scheduler_type = 'constant', # 'cosine', constant warmup_ratio = 0., per_device_train_batch_size = batch_size, # 8, gradient_accumulation_steps = 1, report_to = 'none', do_eval=False, max_steps = max_steps, accelerator_config = {'dispatch_batches':False}, **kwargs )
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My model works fine with adamw_bnb_8bit.
When i switched to galore_adamw_8bit with 'all-linear',
an exception is raised 'can't optimize a non-leaf'
The text was updated successfully, but these errors were encountered: