Create train.py

train.py

@@ -0,0 +1,30 @@
+# train.py
+import time
+import yaml
+
+def train_model(config_file="train.yaml"):
+    print("🧠 Starting training...")
+
+    try:
+        with open(config_file, "r") as f:
+            config = yaml.safe_load(f)
+    except Exception as e:
+        print("⚠️ Failed to load config:", str(e))
+        return f"❌ Failed to load config: {str(e)}"
+
+    model_name = config.get("model", {}).get("name", "default_model")
+    epochs = config.get("training", {}).get("epochs", 5)
+    lr = config.get("training", {}).get("learning_rate", 0.001)
+    batch_size = config.get("training", {}).get("batch_size", 32)
+    device = config.get("training", {}).get("device", "cpu")
+
+    print(f"📦 Model: {model_name}")
+    print(f"🔧 Device: {device}")
+    print(f"📚 Epochs: {epochs}, Batch Size: {batch_size}, Learning Rate: {lr}")
+
+    for epoch in range(1, epochs + 1):
+        print(f"🌀 Epoch {epoch}/{epochs} ...")
+        time.sleep(1)  # Simulate work
+
+    print("✅ Training complete.")
+    return f"✅ Dummy training for `{model_name}` finished on `{device}`!"