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Project: Hundred1

This repository contains the directory structure and data files for the Hundred1 project. Below is a detailed explanation of each folder and its contents.

Directory Structure

hundred1
├── ckpt          # model parameters trained by data
├── data          # Chinese stock market data
├── model         # model code and some running and testing results
├── data2         # US stock market data
│   ├── text
│   └── stock
└── .gitattributes  # initial commit

Folder Explanations

ckpt

This folder contains the model parameters that were trained using the data. These parameters are crucial for replicating the model results and for further training or fine-tuning.

data

This folder includes Chinese stock market data. The data is essential for training and testing models focused on the Chinese stock market.

model

The model folder contains the model code along with some running and testing results. This includes the scripts necessary to build, train, and evaluate the models, as well as any output results from test runs.

data2

The data2 folder is designated for US stock market data. It contains two subdirectories:

text: This subdirectory includes text data related to US stocks.
stock: This subdirectory includes stock data with corresponding time ranges.

Both the text data and stock data in the data2 folder have corresponding time ranges. You can first check the available time ranges and then select and download the data in bulk as needed.

Instructions for Use

Explore Data Ranges: Before downloading data in bulk, it is recommended to first explore the available time ranges. This will help you select the specific data sets that are relevant to your analysis or model training.
Download Data: After identifying the required time ranges, you can proceed to download the data in bulk. Ensure that you have enough storage space and that your internet connection is stable during the download process.
Model Training and Evaluation: Use the data in the data and data2 folders to train and evaluate your models. The model parameters in the ckpt folder can be used to replicate the results or to continue training from a previous state.
Code and Results: Refer to the model folder for all the necessary code and scripts to run the models. The folder also contains results from initial test runs, which can be useful for benchmarking and comparison.

Contribution

If you wish to contribute to this project, please fork the repository, create a new branch, and submit a pull request with your changes. Ensure that your contributions are well-documented and tested.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

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