config.json

{
    "name": "exp-name",
    "n_gpu": 1,
    "arch": {
        "type": "snunlp/KR-ELECTRA-discriminator",
        "args": {
            "gru_enabled": true
        }
    },
    "dataloader": {
        "type": "STSDataModule",
        "args": {
            "batch_size": 16,
            "shuffle": true,
            "dataset_commit_hash": "00e11acc1364f0f222777f8d828e0a8cf0de265c",
            "num_workers": -1,
            "k_fold": {
                "enabled": false,
                "k": 5
            }
        }
    },
    "optimizer": {
        "type": "AdamW",
        "args": {
            "lr": 1e-5,
            "weight_decay": 0,
            "amsgrad": true
        }
    },
    "loss": {
        "type": "SmoothL1Loss",
        "args": {
            "bce": false,
            "beta": 0.5
        }
    },
    "metrics": ["val_pearson"],
    "lr_scheduler": {
        "type": "StepLR",
        "args": {
            "step_size": 50,          
            "gamma": 0.1
        },
        "is_schedule": false
    },
    "trainer": {
        "epochs": 1,
        "save_dir": "saved/models/",
        "save_freq": 1,
        "monitor": "max val_pearson",
        "early_stop": 3
    },
    "wandb": {
        "entity": "salmons",
        "project_name": "sts",
        "sweep_project_name" : "jihwan_sweep",
        "sweep_count": 10
    },
    "sweep_config": {
        "method": "bayes",
        "metric": {
            "name": "val_pearson",
            "goal": "maximize"
        },
        "parameters": {
            "lr": {
                "values": [3e-6, 5e-6, 7e-6, 1e-5, 2e-5, 3e-5, 5e-5]
            },
            "epochs": {
                "values": [4, 5, 6, 7]
            },
            "batch_size" : {
                "values" : [16]
            },
            "loss_function" :{
                "values" : ["SmoothL1Loss"]
            },
            "beta":{
                "values" : [0.1, 0.5, 1.0, 2.0, 5.0]
            },
            "optimizer":{
                "values" : ["AdamW"]
            }
        }
    }
}