peft tensorboard region:us
---
library_name: peft
---
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32
### Framework versions


- PEFT 0.4.0
---
### Args

output_dir=./finetune_weights/lora_model_weights_epochs_1_batch_size_4_gradient_steps_4_lr_0.001_warmup_100/results,
overwrite_output_dir=True,
do_train=False,
do_eval=False,
do_predict=False,
evaluation_strategy=no,
prediction_loss_only=False,
per_device_train_batch_size=4,
per_device_eval_batch_size=8,
per_gpu_train_batch_size=None,
per_gpu_eval_batch_size=None,
gradient_accumulation_steps=4,
eval_accumulation_steps=None,
eval_delay=0,
learning_rate=0.001,
weight_decay=0.0,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
max_grad_norm=1.0,
num_train_epochs=1,
max_steps=-1,
lr_scheduler_type=linear,
warmup_ratio=0.0,
warmup_steps=100,
log_level=passive,
log_level_replica=warning,
log_on_each_node=True,
logging_dir=./finetune_weights/lora_model_weights_epochs_1_batch_size_4_gradient_steps_4_lr_0.001_warmup_100/logs,
logging_strategy=steps,
logging_first_step=False,
logging_steps=100,
logging_nan_inf_filter=True,
save_strategy=steps,
save_steps=10000,
save_total_limit=6,
save_safetensors=False,
save_on_each_node=False,
no_cuda=False,
use_mps_device=False,
seed=42,
data_seed=None,
jit_mode_eval=False,
use_ipex=False,
bf16=False,
fp16=False,
fp16_opt_level=O1,
half_precision_backend=auto,
bf16_full_eval=False,
fp16_full_eval=False,
tf32=None,
local_rank=0,
ddp_backend=None,
tpu_num_cores=None,
tpu_metrics_debug=False,
debug=[],
dataloader_drop_last=False,
eval_steps=None,
dataloader_num_workers=0,
past_index=-1,
run_name=./finetune_weights/lora_model_weights_epochs_1_batch_size_4_gradient_steps_4_lr_0.001_warmup_100/results,
disable_tqdm=False,
remove_unused_columns=True,
label_names=None,
load_best_model_at_end=False,
metric_for_best_model=None,
greater_is_better=None,
ignore_data_skip=False,
sharded_ddp=[],
fsdp=[],
fsdp_min_num_params=0,
fsdp_config={'fsdp_min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False},
fsdp_transformer_layer_cls_to_wrap=None,
deepspeed=None,
label_smoothing_factor=0.0,
optim=adamw_hf,
optim_args=None,
adafactor=False,
group_by_length=False,
length_column_name=length,
report_to=['tensorboard'],
ddp_find_unused_parameters=None,
ddp_bucket_cap_mb=None,
ddp_broadcast_buffers=None,
dataloader_pin_memory=True,
skip_memory_metrics=True,
use_legacy_prediction_loop=False,
push_to_hub=False,
resume_from_checkpoint=None,
hub_model_id=None,
hub_strategy=every_save,
hub_token=None,
hub_private_repo=False,
gradient_checkpointing=False,
include_inputs_for_metrics=False,
fp16_backend=auto,
push_to_hub_model_id=None,
push_to_hub_organization=None,
push_to_hub_token=None,
mp_parameters=,
auto_find_batch_size=False,
full_determinism=False,
torchdynamo=None,
ray_scope=last,
ddp_timeout=1800,
torch_compile=False,
torch_compile_backend=None,
torch_compile_mode=None,
xpu_backend=None,
distributed_state=Distributed environment: NO
Num processes: 1
Process index: 0
Local process index: 0
Device: cuda
,
_n_gpu=1,
__cached__setup_devices=cuda:0,
deepspeed_plugin=None,

