|
|
from transformers import TrainingArguments |
|
|
import os |
|
|
|
|
|
training_args = TrainingArguments( |
|
|
output_dir="./results", |
|
|
num_train_epochs=5, |
|
|
per_device_train_batch_size=8, |
|
|
per_device_eval_batch_size=8, |
|
|
gradient_accumulation_steps=4, |
|
|
learning_rate=3e-5, |
|
|
warmup_ratio=0.1, |
|
|
logging_dir="./logs", |
|
|
logging_steps=100, |
|
|
save_strategy="epoch", |
|
|
evaluation_strategy="epoch", |
|
|
load_best_model_at_end=True, |
|
|
metric_for_best_model="accuracy", |
|
|
greater_is_better=True, |
|
|
fp16=True, |
|
|
dataloader_num_workers=4, |
|
|
group_by_length=True, |
|
|
remove_unused_columns=True, |
|
|
label_smoothing_factor=0.1, |
|
|
gradient_checkpointing=True, |
|
|
optim="adamw_torch", |
|
|
weight_decay=0.01, |
|
|
) |
|
|
|
|
|
|
|
|
training_args.save_to_json("training_args.bin") |
