ner_config.yaml

upload_artifact: false
checkpoint: ~
cuda: 0
checkpoint_path: checkpoints
name: distemist-ner
link: false

run_full_training: false

wand_db_project: 'distemist-ner'

# Default training parameters
output_file : "models"
random_seed: 42
label_all_tokens: false

# Hugging Face training parameters
base_model_checkpoint : PlanTL-GOB-ES/roberta-base-biomedical-clinical-es
batch_size: 32
num_train_epochs: 100
fp16: true
lr_scheduler_type: "linear"
warmup_ratio: 0.0
gradient_checkpointing: true

weight_decay: 0.2
learning_rate: 1e-5
label_smoothing_factor: 0.0

# Checkpointing
save_steps: 10000
keep_all_checkpoints: false

# Hydra settings
version: 1

handlers:
  console:
    class: rich.logging.RichHandler
    
disable_existing_loggers: false

output_base_path: ./outputs/${name}

date_run: ${name}/${now:%Y-%m-%d_%H-%M-%S}

hydra:
  run:
    dir: ${output_base_path}/${now:%Y-%m-%d_%H-%M-%S}
  sweep:
    dir: ./multirun/${name}/${now:%Y-%m-%d_%H-%M-%S}
    subdir: ${hydra.job.num}_${hydra.job.override_dirname}