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config.yaml
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gpu_id: '0'
log_wandb: False
seed: 2024
# ssd4rec settings
hidden_size: 256 # (int) Number of features in the hidden state.
loss_type: 'CE' # (str) Type of loss function. Range in ['BPR', 'CE'].
# SSD Block settings
d_state: 64 # (int) SSM state expansion factor
d_conv: 4 # (int) Local convolution width
expand: 2 # (int) Block expansion factor
headdim: 16 # hidden_size*expand/headdim=multiple of 8
# dataset settings
ml-1m setting:
dataset: ml-1m
MAX_ITEM_LIST_LENGTH: 200 # 200 for MovieLens-1M
dropout_prob: 0.2 # (float) Dropout rate.
norm_embedding: True
beta: 0.1
maskratio: 0.1
num_layers: 2 # (int) Number of Bi-SSD layers.
# # amazon-beauty setting:
# dataset: amazon-beauty
# MAX_ITEM_LIST_LENGTH: 50 # 50 for amazon-beauty datasets
# dropout_prob: 0.4 # (float) Dropout rate.
# norm_embedding: False
# beta: 0.1
# maskratio: 0.2
# num_layers: 1 # (int) Number of Bi-SSD layers.
# # amazon-video-games setting:
# dataset: amazon-video-games
# MAX_ITEM_LIST_LENGTH: 50 # 50 for amazon-video-games datasets
# dropout_prob: 0.4 # (float) Dropout rate.
# norm_embedding: False
# beta: 0.1
# maskratio: 0.1
# num_layers: 1 # (int) Number of Bi-SSD layers.
# kuairand setting
# dataset: kuairand
# MAX_ITEM_LIST_LENGTH: 50 # 50 for kuairand datasets
# dropout_prob: 0.2 # (float) Dropout rate.
# norm_embedding: True
# beta: 0.1
# maskratio: 0.2
# num_layers: 2 # (int) Number of Bi-SSD layers.
USER_ID_FIELD: user_id
ITEM_ID_FIELD: item_id
load_col:
inter: [user_id, item_id, timestamp]
user_inter_num_interval: "[5,inf)"
item_inter_num_interval: "[5,inf)"
# training settings
var_len: True
epochs: 300
train_batch_size: 1024
learner: adam
learning_rate: 0.001
eval_step: 1
stopping_step: 10
train_neg_sample_args: ~
# evalution settings
metrics: ['NDCG', 'MRR', 'Hit']
valid_metric: NDCG@10
eval_batch_size: 2048
weight_decay: 0.0
topk: [10, 20]