defaults:
  - base_config    
  - override data: t5_clap    # change here for loading different text features in training/evaluation
  - override hydra/job_logging: custom  
  - _self_             

hydra:
  run:
    dir: ./exps/${exp_id}  
  output_subdir: train-${now:%Y-%m-%d_%H-%M-%S}-hydra

ema: 
  start: 0

mini_train: False
example_train: False
enable_grad_scaler: True
ac_oversample_rate: 5

log_text_interval: 50
log_extra_interval: 10_000
val_interval: 10_000
eval_interval: 10_000
save_eval_interval: 10_000
save_weights_interval: 5_000
save_checkpoint_interval: 10_000
save_copy_iterations: []

batch_size: 128
eval_batch_size: 4 

num_iterations: 100_000
learning_rate: 1e-4
linear_warmup_steps: 1_000

lr_schedule: step
lr_schedule_steps: [40_000, 45_000]  # this is not used, lr_schedule_steps will be determined by the number of iterations
lr_schedule_gamma: 0.1

clip_grad_norm: 1.0
weight_decay: 1.0e-6

output_name: null   # for eval

use_meanflow: True
use_repa: False