sparse_autoencoder/config.toml

batch_size = 64
steps = 10000
print_every = 500
seed = 1
cnn_storage = "./res/cnn.eqx"

[[sae]]
layer = 6
hidden_size = 256
input_size = 64
learning_rate = 1e-4
l1 = 3e-4
gradually getting there, have yet to get a single trained sae 2023-10-19 17:45:43 +02:00			`batch_size = 64`
sae werks with deep loss 2023-12-23 15:32:18 +01:00			`steps = 10000`
			`print_every = 500`
			`seed = 1`
gradually getting there, have yet to get a single trained sae 2023-10-19 17:45:43 +02:00			`cnn_storage = "./res/cnn.eqx"`
big search for good learning rate 2023-12-13 20:42:30 +01:00
			`[[sae]]`
			`layer = 6`
sae werks with deep loss 2023-12-23 15:32:18 +01:00			`hidden_size = 256`
big search for good learning rate 2023-12-13 20:42:30 +01:00			`input_size = 64`
tensorboard, low l1, lower lr 2023-12-14 13:44:35 +01:00			`learning_rate = 1e-4`
			`l1 = 3e-4`