mindspore/model_zoo/official/nlp/textcnn/subj_config.yaml

# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
enable_modelarts: False
# Url for modelarts
data_url: ""
train_url: ""
checkpoint_url: ""
# Path for local
data_path: "/cache/data"
output_path: "/cache/train"
load_path: "/cache/checkpoint_path/"
device_target: 'Ascend'
enable_profiling: False

# ==============================================================================
# Training options
dataset: 'SUBJ'
pre_trained: False
num_classes: 2
batch_size: 64
epoch_size: 4
weight_decay: 3e-5
keep_checkpoint_max: 1
checkpoint_path: './checkpoint/'
checkpoint_file_path: 'train_textcnn-4_149.ckpt'
word_len: 51
vec_length: 40
base_lr: 1e-3

# Export options
device_id: 0
ckpt_file: ""
file_name: ""
file_format: ""

---
# Help description for each configuration
enable_modelarts: 'Whether training on modelarts, default: False'
data_url: 'Dataset url for obs'
train_url: 'Training output url for obs'
checkpoint_url: 'The location of checkpoint for obs'
data_path: 'Dataset path for local'
output_path: 'Training output path for local'
load_path: 'The location of checkpoint for obs'
device_target: 'Target device type, available: [Ascend, GPU, CPU]'
enable_profiling: 'Whether enable profiling while training, default: False'
dataset: "Dataset to be trained and evaluated, choice: ['MR, SUBJ, SST2']"
train_epochs: "The number of epochs used to train."
pre_trained: 'If need load pre_trained checkpoint, default: False'
num_classes: 'Class for dataset'
batch_size: "Batch size for training and evaluation"
epoch_size: "Total training epochs."
weight_decay: "Weight decay."
keep_checkpoint_max: "keep the last keep_checkpoint_max checkpoint"
num_factors: "The Embedding size of MF model."
checkpoint_path: "The location of the checkpoint file."
eval_file_name: "Eval output file."
checkpoint_file_path: "The location of the checkpoint file."