mirror of
https://github.com/osmarks/nanogpt-experiments.git
synced 2024-09-21 11:49:46 +00:00
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
# train a miniature character-level shakespeare model
|
|
# good for debugging and playing on macbooks and such
|
|
|
|
out_dir = 'out-shakespeare-char'
|
|
eval_interval = 250 # keep frequent because we'll overfit
|
|
eval_iters = 200
|
|
log_interval = 10 # don't print too too often
|
|
|
|
# we expect to overfit on this small dataset, so only save when val improves
|
|
always_save_checkpoint = False
|
|
|
|
wandb_log = False # override via command line if you like
|
|
wandb_project = 'shakespeare-char'
|
|
wandb_run_name = 'mini-gpt'
|
|
|
|
dataset = 'shakespeare_char'
|
|
batch_size = 64
|
|
block_size = 256 # context of up to 256 previous characters
|
|
|
|
# baby GPT model :)
|
|
n_layer = 6
|
|
n_head = 6
|
|
n_embd = 384
|
|
dropout = 0.2
|
|
|
|
learning_rate = 1e-3 # with baby networks can afford to go a bit higher
|
|
max_iters = 5000
|
|
lr_decay_iters = 5000 # make equal to max_iters usually
|
|
min_lr = 1e-4 # learning_rate / 10 usually
|
|
beta2 = 0.99 # make a bit bigger because number of tokens per iter is small
|
|
|
|
warmup_iters = 100 # not super necessary potentially
|
|
|
|
# on macbook also add
|
|
# device = 'cpu' # run on cpu only
|
|
# compile = False # do not torch compile the model
|