- This repo releases the implementation for our experiments of the research paper: "Instruction Tuned Models are Quick Learners"
- The experiments are run on Tk-instruct-3B-model, which was finetuned on data.
The experiments and analysis are conducted on the following environment:
- CUDA (11.1)
- cuDNN (8.0)
- Pytorch (1.10.0)
- Transformers (4.18.0)
- DeepSpeed
For cloning the environment and install the required python libraries run the following command:
pip install -r requirements.txt
Our model are trained on the Super-NaturalInstructions English-only tasks on 119 test tasks. The data splits can be created by running the following python script.
python data_prep.py --num_examples 2 --ten True --onepercent True --hundred True --twohundred True --thousand True
To run the experiment, run the following the command:
sh scripts/master.sh -t task.txt -s twohundred
The above command will finetune the model(s) and evaluate it.