cora.yaml

# @package _global_

# to execute this experiment run:
# python train.py experiment=example

defaults:
  - override /datamodule: cora.yaml
  - override /model: cora.yaml
  - override /callbacks: default.yaml
  - override /logger: null
  - override /trainer: default.yaml
  - override /paths: default.yaml
# all parameters below will be merged with parameters from default configurations set above
# this allows you to overwrite only specified parameters

# name of the run determines folder name in logs
name: "bert_token_classifier"

seed: 777

trainer:
  min_epochs: 5
  max_epochs: 15
  gradient_clip_val: 0.5

module:
  lr: 2e-5
  model:
    model_checkpoint: ${paths.root_dir}/models/default/scibert-synthetic-uncased-200k
    output_size: 13
    cache_dir: ${paths.root_dir}/.cache/

datamodule:
  data_repo: "myvision/cora-dataset-final"
  train_batch_size: 8
  num_workers: 0
  pin_memory: False
  data_cache_dir: ${paths.data_dir}/cora/

logger:
  wandb:
    tags: ["cora", "${name}"]

paths:
  #path to save pretrained models
  model_dir: ${paths.root_dir}/models/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}