Update README.md
Browse files基于图像分类模型"microsoft/resnet-50"进行微调，数据使用"yuean/EuroSAT-2750"，使用Trainer进行简单训练:
checkpoint = "microsoft/resnet-50"
model = AutoModelForImageClassification.from_pretrained(
checkpoint,
num_labels=len(labels),
id2label=id2label,
label2id=label2id,
ignore_mismatched_sizes=True,
)
training_args = TrainingArguments(
output_dir="my_resnet50_model",
remove_unused_columns=False,
evaluation_strategy="epoch",
save_strategy="epoch",
learning_rate=5e-5,
per_device_train_batch_size=16,
gradient_accumulation_steps=4,
per_device_eval_batch_size=16,
num_train_epochs=3,
warmup_ratio=0.1,
logging_steps=10,
load_best_model_at_end=True,
metric_for_best_model="accuracy",
push_to_hub=True,
)
accuracy = evaluate.load("accuracy")
def compute_metrics(eval_pred):
predictions, labels = eval_pred
predictions = np.argmax(predictions, axis=1)
return accuracy.compute(predictions=predictions, references=labels)
trainer = Trainer(
model=model,
args=training_args,
data_collator=data_collator,
train_dataset=dataset["train"],
eval_dataset=dataset["test"],
tokenizer=image_processor,
compute_metrics=compute_metrics,
)
trainer.train()