use_wandb = 1
seed = 1
style = "dit"
d_adapter = 512
normalize_embeddings = 1
depth = 2
embs = [ "gte", "gtr", "stella", "sentence-t5", "e5", "sbert", "clip", "stella-big", "snowflake", "ember",]
n_embs_per_batch = 2
max_seq_length = 512
depth_transform = 4
lr = 5e-5
bs = 128
save_every = 400
epochs = 5.0
dataset = "nomic_unsupervised"
max_grad_norm = 10.0
gradient_accumulation_steps = 1
loss_coefficient_vsp = 0
loss_coefficient_contrastive = 1
loss_coefficient_trans = 1
loss_coefficient_cc = 0
eval_steps = 99999999999999999
cluster_size = 1024
cluster_strategy = "cluster_within_domain"
warmup_steps = 100
wandb_project = "edx-2"
wandb_name = "dit-pretrain-sm-1"
save_dir = "checkpoints/{}/"
num_params = 391411032