# REPLACE WITH YOURS
user='ps-autoregressive' #YOUR WANDB USERNAME
data_dir='/shared/share_mala/implicitbayes/dataset_files/MIND_data/filter100/models/0327_bert_marginal_split_v2/marginal:epochs=500,bs=100,lr=1e-05,wd=0.01,MLP_layers=3,MLP_width=100,weight_factor=1,max_obs=500,repeat_suffstat=1,datasplit=first_100,bert_lr=1e-05,sample_frac=1.0,p_alpha=1,seed=2340923'

marginal_vs_sequential='marginal'
save_name='ensembles_randprior'
MLP_width=100
MLP_layer=3
batch_size=100
repeat_suffstat=1
eval_batch_size=100
transform_success_p_alpha=1
lr=1e-5
bert_lr=1e-8
wd=1e-2
sample_frac=1
num_loader_obs=500
num_loader_obs_train=500
epochs=50
embed_data_dir=True
rand_prior=1
for boot_seed in {0..50} 
do
    python train_models.py --save_name $save_name --wandb_entity $wandb_entity --data_dir $data_dir --marginal_vs_sequential $marginal_vs_sequential --MLP_width $MLP_width --MLP_layer $MLP_layer --batch_size $batch_size --repeat_suffstat $repeat_suffstat --eval_batch_size $eval_batch_size --transform_success_p_alpha 1 --learning_rate $lr --bert_learning_rate $bert_lr --weight_decay $wd --sample_frac $sample_frac --num_loader_obs $num_loader_obs --num_loader_obs_train $num_loader_obs_train --epochs $epochs --embed_data_dir $embed_data_dir --bootstrap_seed $boot_seed --seed $boot_seed --rand_prior $rand_prior
done

