seed: 101112

### model
model_name_or_path: meta-llama/Meta-Llama-3-8B-Instruct
trust_remote_code: true
flash_attn: auto
use_cache: false

### method
stage: sft
do_train: true
finetuning_type: lora
lora_rank: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target: k_proj,v_proj,down_proj

### dataset
dataset: hellaswag
template: llama3
cutoff_len: 2048
overwrite_cache: true
preprocessing_num_workers: 8
dataloader_num_workers: 2
packing: false

### output
output_dir: saves_multiple/lora/llama-3-8b-instruct/train_hellaswag_101112_1760638083
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: 4
learning_rate: 5.0e-5
num_train_epochs: 20
weight_decay: 1.0e-5
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: lora_llama-3-8b-instruct_train_hellaswag_101112_1760638083

### eval
per_device_eval_batch_size: 4
eval_strategy: steps
eval_steps: 0.05
val_size: 0.1