Seed_Cup_TextCNN

https://github.com/Dedsec-Xu/Seed_Cup_TextCNN

Code for Seed Cup Machine Learning competetion. We developed a CNN NLP model which can process Masked Data of a product description and decide the category of the product. The final score is 86.04%.

Example

By analyzing this:

We get the category of the product

Category

data/: stores dataset

model/: stores model

config.py: configuration file

class_idx.py: to map the output number to product category

word_idx.py: use onehot to generate number

accurancy.py: F1 class uses save_data to save data from batch and caculate_f1 calculates f1

Dataloader.py: load files

main.py: include train() and val()

test.py: generate test results

word_preprocess.py: process dataset and generate npy for data analyze

word_plot.py: visualize words

word_delete.py: delete a specific word in dataset

word_delete_high_freq.py: calculate words over thereshold and save them into npy

connect_all.py: to put two datasets together. This give us 0.82 improvement

Output Score

Output achieved 0.8604 f_point

f1_cate1: 0.9577

f1_cate2: 0.8884

f1_cate3: 0.8302

Instruction

Use python main.py to train

Use python test.py to run test

Enviorment

Ubuntu 18.04

python:3.7.6

cuda:9.0.176

torch 0.4.1