```
training_arguments = transformers.TrainingArguments(
    per_device_train_batch_size=4,
    gradient_accumulation_steps=BATCH_SIZE // MICRO_BATCH_SIZE,
    warmup_steps=100,
    max_steps=300,
    learning_rate=3e-4,
    fp16=True,
    logging_steps=10,
    optim="adamw_torch",
    evaluation_strategy="steps",
    save_strategy="steps",
    eval_steps=50,
    save_steps=50,
    save_total_limit=3,
    load_best_model_at_end=True,
)

LORA_R = 8
LORA_ALPHA = 16
LORA_DROPOUT= 0
LORA_TARGET_MODULES = [
    "q_proj",
    "v_proj",
]

BATCH_SIZE = 128
MICRO_BATCH_SIZE = 4
GRADIENT_ACCUMULATION_STEPS = BATCH_SIZE // MICRO_BATCH_SIZE
LEARNING_RATE = 3e-4
TRAIN_STEPS = 300
```