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best_hyperparameters.md
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Number of Optuna trials: 25
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Best trial objective: 0.5624 (best trial number: 3)
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Best hyperparameters:
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- learning_rate: 0.00010780369551982127
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- warmup_ratio: 0.05
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- min_lr: 1.8229175490752733e-09
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- factor: 0.8500000000000001
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Training arguments:
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- output_dir: /mimer/NOBACKUP/groups/naiss2023-6-290/stefano/models//PROTAC-Splitter-EncoderDecoder-lr_reduce-opt25
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- learning_rate: 5e-05
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- optim: adamw_torch
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- lr_scheduler_type: reduce_lr_on_plateau
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- lr_scheduler_kwargs: {'min_lr': 1e-06}
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- adam_beta1: 0.9
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- adam_beta2: 0.999
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- adam_epsilon: 1e-08
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- batch_eval_metrics: False
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- group_by_length: True
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- per_device_train_batch_size: 128
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- per_device_eval_batch_size: 64
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- gradient_accumulation_steps: 1
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- auto_find_batch_size: True
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- fp16: True
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- fp16_full_eval: True
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- half_precision_backend: auto
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- use_cpu: False
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- dataloader_num_workers: 8
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- dataloader_prefetch_factor: None
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- max_steps: 10000
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- num_train_epochs: -1
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- save_steps: 5000
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- save_strategy: steps
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- eval_steps: 2500
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- eval_delay: 5000
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- eval_strategy: steps
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- save_total_limit: 2
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- load_best_model_at_end: True
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- metric_for_best_model: all_ligands_equal
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- include_inputs_for_metrics: True
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- eval_on_start: False
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- log_level: debug
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- logging_steps: 500
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- disable_tqdm: True
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- report_to: ['tensorboard']
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- save_only_model: False
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- push_to_hub: True
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- push_to_hub_model_id: PROTAC-Splitter-EncoderDecoder-lr_reduce-opt25
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- push_to_hub_organization: ailab-bio
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- hub_model_id: ailab-bio/PROTAC-Splitter-EncoderDecoder-lr_reduce-opt25
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- hub_strategy: checkpoint
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- hub_private_repo: True
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- seed: 42
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- data_seed: 42
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- warmup_steps: 0
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- generation_config: GenerationConfig {
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"max_length": 512,
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"max_new_tokens": 512
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}
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- predict_with_generate: True
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- generation_max_length: 512
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