erniesage_node_classfication.yaml

# Global Enviroment Settings 
#
# trainer config ------
task: "node_classification"
learner_type: "gpu"
optimizer_type: "adam"
lr: 0.00005
batch_size: 32
CPU_NUM: 10
epoch: 3
log_per_step: 1
save_per_step: 1000
output_path: "./output"
ckpt_path: "./ernie_base_ckpt"

# data config ------
graph_data: "./example_data/node_classification/graph_data.txt"
train_data: "./example_data/node_classification/train_data.txt"

graph_work_path: "./workdir"
sample_workers: 1
use_pyreader: true
input_type: "text"

# model config ------
num_label: 10
samples: [10]
model_type: "ERNIESageV2"
layer_type: "graphsage_sum"

max_seqlen: 40

num_layers: 1
hidden_size: 128
final_fc: true
final_l2_norm: true
loss_type: "softmax_with_cross_entropy"
margin: 0.1
neg_type: "batch_neg"

# infer config ------
infer_model: "./output/last"
infer_batch_size: 128

# ernie config ------
encoding: "utf8"
ernie_vocab_file: "./vocab.txt"
ernie_config:
    attention_probs_dropout_prob: 0.1
    hidden_act: "relu"
    hidden_dropout_prob: 0.1
    hidden_size: 768
    initializer_range: 0.02
    max_position_embeddings: 513
    num_attention_heads: 12
    num_hidden_layers: 12
    sent_type_vocab_size: 4
    task_type_vocab_size: 3
    vocab_size: 18000
    use_task_id: false
    use_fp16: false