You may see the report if you follow this link

Firstly, install needed requirements for running model

pip install -r ./requirements.txt

Use bash script to download trained model

cd ./default_test_model
./download.sh

It will be placed to ./default_test_model/checkpoint.pth

If you have some issues using bash utilities, you may download model directly from google drive

python test.py \
   -c default_test_model/config.json \
   -r default_test_model/checkpoint.pth \
   -t test_data \
   -o test_result.json

This repository is based on a heavily modified fork of pytorch-template repository.

You can use this project with docker. Quick start:

docker build -t my_src_image .
docker run \
   --gpus '"device=0"' \
   -it --rm \
   -v /path/to/local/storage/dir:/repos/asr_project_template/data/datasets \
   -e WANDB_API_KEY=<your_wandb_api_key> \
	my_src_image python -m unittest

Notes:

• -v /out/of/container/path:/inside/container/path -- bind mount a path, so you wouldn't have to download datasets at the start of every docker run.
• -e WANDB_API_KEY=<your_wandb_api_key> -- set envvar for wandb (if you want to use it). You can find your API key here: https://wandb.ai/authorize