Configure μP For Bert Pretrain Beta
Note: Beta support indicates that we have confirmed the model’s μP functionality using coordinate checks, but have yet to perform long convergence runs.
Model Params
-
mup_base_hidden_size
(Required to enable μP):The hidden size of the proxy model in μP transfer used to calculate the necessary multipliers. -
mup_base_filter_size
(Required to enable μP):The filter size of the proxy model in μP transfer used to calculate the necessary multipliers. -
embeddings_scale
:Scales the embedding hidden states (i.e. the tensor after embeddings & embedding layer norm are applied). Recommended to tune for stabilizing gradient flow during μP training. -
output_logits_alpha
:Constant applied to the output logits scalar in μP training. The output logits are scaled byoutput_logits_alpha * mup_base_hidden_size/hidden_size
. Recommended to tune for stabilizing output logits in μP training. -
scale_qk_dot_by_d
:Scales attention QK dot product by d instead of sqrt(d). Must be enabled for muP training. -
attention_logits_alpha
:Scales the attention QK dot product by the specified value. Recommended to tune for stabilizing attention logits in muP training. -
scale_output_logits_by_d
:Scales the output logits in μP bymup_base_hidden_size/hidden_size
if True andsqrt(mup_base_hidden_size/hidden_size)
if False. It is traditionally set toTrue
in the μP implementation of this model.
Supported LR Adjustment Groups
-
embedding
: Targets the embedding weights. -
encoder_attention
: Targets the dense layers in the encoder (Q, K, V, Output projections) -
encoder_input_ffn
: Targets the first of the two FFN blocks in the encoder. -
encoder_output_ffn
: Targets the final FFN block in the encoder. -
pooler
: Targets the pooler FFN.
Example Configuration
Note how not all the LR adjustment groups were specified since there is only a need to provide these values in the config if you would like to override the traditional μP LR scaling.