/
settings.py
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/
settings.py
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# BO settings that may be overridden
DEFAULT_BO_SETTINGS = {
"MODEL_KWARGS": {
"warmup_steps": 128,
"num_samples": 64,
"thinning": 4,
},
"ACQF_OPTIM_KWARGS": {
"max_eval": 2000,
"n_restart": 10
},
}
# task specific settings
TASK_SETTINGS = {
"mrpc": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
"num_steps_per_save": 115,
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"ref_point": [26., 0.7],
"objectives": ["param", "acc"],
# "low_resource": 100
},
"sst2": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
"num_steps_per_save": 1,
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"ref_point": [26., 0.7],
"objectives": ["param", "acc"]
},
"qnli": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [26., 0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["param", "acc"]
},
"qqp": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 115,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [26., 0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["param", "acc"],
# "low_resource": 100
},
"mnli": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [26., 0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["param", "acc"]
},
"cola": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [26., 0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["param", "acc"]
},
"rte": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [26., 0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["param", "acc"]
},
"stsb": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [26., 0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["param", "acc"]
}
# Add new task configs here
}
TASK_SETTINGS_SO = {
"mrpc": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
"num_steps_per_save": 115,
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"ref_point": [0.7],
"objectives": ["acc"],
# "low_resource": 100
},
"sst2": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
"num_steps_per_save": 1,
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"ref_point": [0.7],
"objectives": ["acc"]
},
"qnli": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["acc"]
},
"qqp": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 115,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["acc"],
# "low_resource": 100
},
"mnli": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["acc"]
},
"cola": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["acc"]
},
"rte": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["acc"]
},
"stsb": {
"num_epochs": 20,
"patience": 10,
"save_type": "epoch",
"num_steps_per_save": 1,
# in low resource, we need to set this accordingly 25 for 10ep in 300; 50 for 20ep in 300.
# 20 for 20epocch in 100. 160 for 20 epoch in 1000. 80for 20 epoch in 500.20 for 20 epochs in 100
"ref_point": [0.7],
# <- set this to the nadir point by doing some random sampling in the task. Not required for single task optimization
"objectives": ["acc"]
}
# Add new task configs here
}