cutoff_len: 2048
dataset: treino_pt_rde
dataset_dir: data
ddp_timeout: 180000000
do_train: true
finetuning_type: lora
flash_attn: auto
fp16: true
gradient_accumulation_steps: 4
learning_rate: 3.0e-05
logging_steps: 10
lora_alpha: 16
lora_dropout: 0
lora_rank: 8
lora_target: all
lr_scheduler_type: cosine
max_grad_norm: 1.0
max_samples: 3716
model_name_or_path: google/gemma-2-9b-it
num_train_epochs: 3.0
optim: adamw_torch
output_dir: saves/Gemma-2-9B-Instruct/lora/gemma2-9b-finetuned
packing: false
per_device_train_batch_size: 8
plot_loss: true
preprocessing_num_workers: 16
quantization_bit: 4
quantization_method: bitsandbytes
report_to: none
save_steps: 1000
stage: sft
template: alpaca
use_unsloth: true
warmup_steps: 0