from transformers import PretrainedConfig
class TunBertConfig(PretrainedConfig):
    model_type = "bert"
    def __init__(self, 
                attention_probs_dropout_prob = 0.1,
                classifier_dropout = None,
                gradient_checkpointing = False,
                hidden_act = "gelu",
                hidden_dropout_prob = 0.1,
                hidden_size = 768,
                initializer_range = 0.02,
                intermediate_size = 3072,
                layer_norm_eps =  1e-12,
                max_position_embeddings =  512,
                model_type =  "bert",
                num_attention_heads = 12,
                num_hidden_layers = 12,
                pad_token_id =  0,
                position_embedding_type =  "absolute",
                transformers_version =  "4.35.2",
                type_vocab_size = 2,
                use_cache = True,
                vocab_size = 30522, 
                **kwargs):
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.classifier_dropout = classifier_dropout
        self.gradient_checkpointing = gradient_checkpointing
        self.hidden_act = hidden_act
        self.hidden_dropout_prob = hidden_dropout_prob
        self.hidden_size = hidden_size
        self.initializer_range = initializer_range
        self.intermediate_size = intermediate_size
        self.layer_norm_eps = layer_norm_eps
        self.max_position_embeddings = max_position_embeddings
        self.model_type = model_type
        self.num_attention_heads = num_attention_heads
        self.num_hidden_layers = num_hidden_layers
        self.pad_token_id = pad_token_id
        self.position_embedding_type = position_embedding_type
        self.transformers_version = transformers_version
        self.type_vocab_size = type_vocab_size
        self.use_cache = use_cache
        self.vocab_size = vocab_size
        super().__init__(**kwargs)