Music Tagging Distributed Training with Accelerate

This repository contains an example of distributed training for music tagging using the Accelerate framework. It demonstrates how to set up multi-machine, multi-GPU distributed training.

Setup Instructions

Please follow the steps below on both machines to set up and run the training process:

1. Clone the repository:

   git clone https://github.com/HarlandZZC/music_tagging_accelerate.git
   cd music_tagging_accelerate

2. Set up the environment:

   conda env create -f music_tagging_env.yaml
   conda activate music_tagging

   If some packages cannot be installed through the YAML file, please download them manually.

3. Adjust the default_config.yaml and train.sh according to the server you are using.

4. Start training by running:

   bash train.sh

5. To evaluate the training results, run:

   python test.py

Please note that test.py only runs on a single GPU on a single machine. For more information on how to use the Accelerate framework, please refer to https://huggingface.co/docs/accelerate/index.