dr_bptf.yaml

# general
gpu_id: 0
use_gpu: True
seed: 2022
state: INFO
reproducibility: True
data_path: 'dataset/'
checkpoint_dir: 'saved'
show_progress: False
save_dataset: False
dataset_save_path: ~
save_dataloaders: False
dataloaders_save_path: ~
log_wandb: False
wandb_project: 'recbole'
LABEL_FIELD : 'rating'
RATING_FIELD : 'rating'
TIME_FIELD: 'wday'
#WDAY_FIELD: 'wday'
# training settings
epochs: 300
train_batch_size: 2048
learner: adam
base_learning_rate: 0.001
imp_learning_rate: 0.01
neg_sampling: ~
#  uniform: 10

eval_step: 1
stopping_step: 10
clip_grad_norm: ~
# clip_grad_norm:  {'max_norm': 5, 'norm_type': 2}
weight_decay: 0.0
loss_decimal_place: 4
require_pow: False

# evaluation settings
eval_args: 
  split: {'RS':[0.8,0.1,0.1]}
  group_by: user
  order: TO
  mode: labeled
repeatable: False
metrics: ["MSE","RMSE","MAE","AUC","LogLoss"]
topk: [10]
load_col:  {'inter': ['user_id', 'item_id','rating','timestamp','wday']}
valid_metric: rmse
valid_metric_bigger: True
eval_batch_size: 2048
metric_decimal_place: 4
normalize_field: ['timestamp']
normalize_all: ~
K: 7
T: 100
M: 3
sig: 0.5
embedding_size: 16
benchmark_filename: ['train','valid','test']

sample_rate: 0.1
ips_freq: 2
imp_freq: 2
base_freq: 1
gamma_v: 1.1
gamma_t: 1.1
task: 'dr'
robust: False
psv_path: 'init_ps/food_item_ps_week.pth'
pst_path: 'init_ps/food_time_ps_week.pth'