Simple Yaml example

In this simple experiment, we will: 1. Use the toys Amazon Dataset and add item_ and user_ prefixes to each item and user ids 2. Train the GPT2Rec using the distilgpt2 checkpoint on the SequentialSideInfoTask 3. Evaluate results using hit@10 and hit@5 metrics

Info

Please remember that to invoke LaikaLLM using the .yaml configuration, the working directory should be the repository root!

Yaml config

Define your custom params.yml:

params.yml

exp_name: simple_exp
device: cuda:0
random_seed: 42

data:
  AmazonDataset:
    dataset_name: toys
    add_prefix_items_users: true

model:
  GPT2Rec:
    name_or_path: "distilgpt2"
  n_epochs: 10
  train_batch_size: 8
  train_tasks:
    - SequentialSideInfoTask

eval:
  eval_batch_size: 4
  eval_tasks:
    SequentialSideInfoTask:
      - hit@10
      - hit@5

Invoke LaikaLLM

After defining the above params.yml, simply execute the experiment with

Run the experiment

python laikaLLM.py -c params.yml

The model trained and the evaluation results will be saved into models and reports/metrics