config.json

{
  "model_type": "CustomModel",
  "input_size": 768,
  "hidden_size": 128,
  "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."
}