ADPrLlama / training_args.yaml
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bf16: true
cutoff_len: 2048
dataset: adpr_train
dataset_dir: data
ddp_timeout: 180000000
do_train: true
eval_steps: 100
eval_strategy: steps
finetuning_type: lora
flash_attn: auto
gradient_accumulation_steps: 8
include_num_input_tokens_seen: true
learning_rate: 5.0e-05
logging_steps: 5
lora_alpha: 128
lora_dropout: 0.01
lora_rank: 64
lora_target: q_proj,v_proj,k_proj,o_proj,gate_proj,down_proj,up_proj
lr_scheduler_type: cosine
max_grad_norm: 1.0
max_samples: 100000
model_name_or_path: GreatCaptainNemo/ProLLaMA
num_train_epochs: 3.0
optim: adamw_torch
output_dir: saves/Custom/lora/train_2025-04-05-23-57-03
packing: false
per_device_eval_batch_size: 16
per_device_train_batch_size: 16
plot_loss: true
preprocessing_num_workers: 16
report_to: none
resize_vocab: true
save_steps: 100
stage: sft
template: alpaca
trust_remote_code: true
val_size: 0.1
warmup_steps: 20