base_timesvd.yaml

# general
gpu_id: 2
use_gpu: True
seed: 2020
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: 100
train_batch_size: 1024
learner: adam
learning_rate: 0.001
neg_sampling: ~
#  uniform: 10

eval_step: 1
stopping_step: 50
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: 1024
metric_decimal_place: 4
normalize_field: ['timestamp']
normalize_all: ~
K: 7
T: 100
M: 3
sig: 0.5
embedding_size: 64
benchmark_filename: ['train','valid','test']