66 lines
1.8 KiB
YAML
66 lines
1.8 KiB
YAML
seed: 42
|
|
|
|
### model
|
|
model_name_or_path: meta-llama/Llama-3.2-1B-Instruct
|
|
trust_remote_code: true
|
|
flash_attn: auto
|
|
use_cache: false
|
|
|
|
### method
|
|
# Full fine-tune of every decoder block, but with the (tied) embeddings frozen.
|
|
# `finetuning_type: freeze` only trains modules whose name matches a trainable layer;
|
|
# embed_tokens / lm_head / final model.norm are "extra" modules and stay frozen unless
|
|
# listed in freeze_extra_modules. Setting freeze_trainable_layers = num_hidden_layers (16
|
|
# for Llama-3.2-1B) makes ALL decoder blocks trainable, so this == "full FT minus
|
|
# embeddings". Because tie_word_embeddings=true, freezing embed_tokens also freezes lm_head.
|
|
# This is lever B of the embedding-amplification fix (see figures/amplification/README.md).
|
|
stage: sft
|
|
do_train: true
|
|
finetuning_type: freeze
|
|
freeze_trainable_layers: 16
|
|
freeze_trainable_modules: all
|
|
# freeze_extra_modules: left unset -> embed_tokens, lm_head (tied), final norm stay frozen
|
|
|
|
### dataset
|
|
dataset: record
|
|
template: llama3
|
|
cutoff_len: 2048
|
|
overwrite_cache: true
|
|
preprocessing_num_workers: 4
|
|
dataloader_num_workers: 4
|
|
packing: false
|
|
|
|
### output
|
|
output_dir: saves_bts_preliminary/freeze/llama-3.2-1b-instruct/train_record_42_1779354540
|
|
logging_steps: 5
|
|
save_steps: 0.05
|
|
overwrite_output_dir: true
|
|
save_only_model: false
|
|
plot_loss: true
|
|
include_num_input_tokens_seen: true
|
|
push_to_hub: true
|
|
push_to_hub_organization: rbelanec
|
|
load_best_model_at_end: true
|
|
save_total_limit: 1
|
|
|
|
### train
|
|
per_device_train_batch_size: 8
|
|
learning_rate: 2.0e-6
|
|
num_train_epochs: 1
|
|
weight_decay: 1.0e-2
|
|
lr_scheduler_type: cosine
|
|
bf16: true
|
|
ddp_timeout: 180000000
|
|
resume_from_checkpoint: null
|
|
warmup_ratio: 0.1
|
|
optim: adamw_torch
|
|
report_to:
|
|
- wandb
|
|
run_name: freeze_llama-3.2-1b-instruct_train_record_42_1779354540
|
|
|
|
### eval
|
|
per_device_eval_batch_size: 8
|
|
eval_strategy: steps
|
|
eval_steps: 0.05
|
|
val_size: 0.1
|