Create Y2

Y2

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+training_args = TrainingArguments(
+    output_dir="my_awesome_food_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,
+)
+
+trainer = Trainer(
+    model=model,
+    args=training_args,
+    data_collator=data_collator,
+    train_dataset=food["train"],
+    eval_dataset=food["test"],
+    tokenizer=image_processor,
+    compute_metrics=compute_metrics,
+)
+
+trainer.train()