get_started.md

Get Started

Install PyTorch. The code has been tested with CUDA 11.2/CuDNN 8.1.0, PyTorch 1.8.1.

First, prepare pre-training datasets and downstream classification datasets through get_started.md.

We organize the different models trained on different data through separate [experimental catalogs] (experiments/), you can check the dir for detail.

1. Pre-training

You can run run.sh directly to train the corresponding model. We train most of our models on 4x8-gpu nodes. Check the config in the experiment directory of the corresponding model for details.

2. Zero-shot Evalution

You can add a argument --evaluate on run script for zero-shot evalution. There are two ways to set the model file location:

• Move the checkpoint file to the corresponding experiment directory and rename it to checkpoints/ckpt.pth.tar

• Change the config file:

...
...
saver:
    print_freq: 100
    val_freq: 2000
    save_freq: 500
    save_many: False
    pretrain:
        auto_resume: False
        path: /path/to/checkpoint