Create train_dpo.py

train_dpo.py

@@ -0,0 +1,48 @@
+from datasets import load_dataset
+from transformers import AutoTokenizer, AutoModelForCausalLM, TrainingArguments
+from trl import DPOTrainer
+
+# --------------------
+# 1. USTAW MODEL
+# --------------------
+model_name = "mistralai/Mistral-7B-Instruct-v0.2"  # możesz zmienić
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    load_in_4bit=True,
+    device_map="auto"
+)
+
+# --------------------
+# 2. WCZYTAJ DANE
+# --------------------
+dataset = load_dataset("json", data_files="dpo_data.jsonl")["train"]
+
+# --------------------
+# 3. ARGUMENTY TRENINGU
+# --------------------
+training_args = TrainingArguments(
+    output_dir="./dpo_output",
+    per_device_train_batch_size=2,
+    gradient_accumulation_steps=4,
+    num_train_epochs=2,
+    learning_rate=5e-6,
+    bf16=True,
+    logging_steps=10,
+    save_steps=500,
+)
+
+# --------------------
+# 4. START DPO
+# --------------------
+trainer = DPOTrainer(
+    model=model,
+    ref_model=None,
+    tokenizer=tokenizer,
+    train_dataset=dataset,
+    beta=0.1,
+    args=training_args,
+)
+
+trainer.train()