a_informed-meta-learning_p/config_atom3d_lba_poc.toml at main · harinu123/a_informed-meta-learning_p · GitHub

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project_name = "INP_ATOM3D_LBA_POC"
seed = 0
load_it = "best"
batch_size = 16
num_epochs = 200
lr = 0.0003
decay_lr = 10
sort_context = false
train_split = "train"
val_split = "val"
n_trials = 1
beta = 1.0
run_name_prefix = "inp"
run_name_suffix = "atom3d_lba_poc"

train_num_z_samples = 1
test_num_z_samples = 16

freeze_llm = true
tune_llm_layer_norms = false

dataset = "atom3d-lba-poc"
data_root = "data/atom3d_lba_poc"
min_num_context = 0
max_num_context = 16
num_targets = 32
x_sampler = "uniform"
noise = 0.0

input_dim = 300
output_dim = 1

use_knowledge = true
text_encoder = "none"
knowledge_merge = "concat"
knowledge_dropout = 0.2
knowledge_extractor_num_hidden = 0
knowledge_dim = 128

hidden_dim = 128
xy_encoder_num_hidden = 2
xy_encoder_hidden_dim = 128
xy_self_attention = "none"
xy_self_attention_num_layers = 1
latent_encoder_num_hidden = 1
decoder_hidden_dim = 128
decoder_num_hidden = 3
decoder_activation = "gelu"
x_transf_dim = 128
x_encoder_num_hidden = 1
data_agg_func = "mean"
path = "latent"