Update config.json

config.json

@@ -1,15 +1,15 @@
 {
   "model_type": "CustomModel",
-  "architecture": "CustomModel",
-  "input_size": 512,
+  "input_size": 768,
   "hidden_size": 128,
-  "output_size": 768,
-  "vocab_size": 30522,  // Example vocab size, adjust according to your tokenizer's vocabulary
-  "layer_norm_epsilon": 1e-12,
-  "hidden_dropout_prob": 0.1,
-  "num_attention_heads": 12,  // Adjust if your model uses attention mechanisms
-  "attention_probs_dropout_prob": 0.1,
-  "intermediate_size": 3072,  // Example size, adjust based on your model's architecture
-  "num_hidden_layers": 12,  // Adjust based on your model's depth
-  "initializer_range": 0.02
+  "output_size": 2,
+  "a": 0.5,
+  "epsilon": 0.1,
+  "init_weights_range": "-1 to 1",
+  "architecture": "Single layer linear transformation followed by Ba-inspired activation and another linear transformation.",
+  "activation_function": "Ba-inspired custom activation",
+  "num_labels": 2,
+  "problem_type": "Classification",
+  "vocab_size": 30522,  // Assuming you're using a tokenizer similar to BERT's; adjust accordingly.
+  "_comment": "This is a custom model configuration. Some fields are specific to this custom implementation and may require custom handling code."
 }