## Question 3 of APOAI2025 Mock Competition: News Text Classification Task

**Introduction**:  This is the Question 3 of APOAI2025 Mock Competition, and it is also the third question of the NOAI2024(China).

### I. Question Overview

A dataset for news text classification is provided, which is stored in a .csv file and contains two variables:

* **text**: The content of the news text.
* **category**: The category of the news text.

The training set (Training Set) is stored in train_news.csv, with a total of 1,000 samples. The testing set (Testing Set) is stored in test_news.csv, with a total of 200 samples. During the competition, the test set samples without labels will be provided.


### II. Data Set

1. Address of the training set: train_news.csv, [Training Set](https://bohrium.dp.tech/competitions/2223242868?tab=datasets);
2. Test set (without labels): test_news_nolabel.csv, which contestants cannot access or download;
3. Test set (with labels): test_news_label.csv, which contestants cannot access or download.


### III. Task

Please use PyTorch to design and train a natural language processing model to achieve the news text classification task, that is, input the sentences of the news and output the news categories.

The specific requirements are as follows:

1. The total training time and testing time using the CPU should not exceed 10 minutes. The connection time and queuing time are not counted into the total time.
2. Tip: It is recommended to use Word Embedding + LSTM.

### IV. Submission

Please submit the submission.ipynb file, which contains the entire process of training the model. In submission.ipynb, store the prediction results of the test set in submission.csv. The naming and storage method of the label should be consistent with that of train_news.csv.

You can refer to the submission format in baseline.ipynb. The address of baseline.ipynb: [Question 3 of APOAI Mock Competition_baseline](https://bohrium.dp.tech/notebooks/84584239178)


### V. Scoring

1. When the training and testing are completed within the specified time, the scoring criterion is the average value of the F1-Scores of all categories. Please look up the meaning of F1-Score on the Internet by yourself.

2. If the F1-Scores of all categories are not calculated, a score of 0 will be given.

3. If the total time for training and testing exceeds the time limit, a score of 0 will be given.