Upload MyBertClassifier

config.json

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+{
+  "architectures": [
+    "MyBertClassifier"
+  ],
+  "auto_map": {
+    "AutoConfig": "configuration_my_bert_classifier.MyBertClassifierConfig",
+    "AutoModel": "modeling_my_bert_classifier.MyBertClassifier"
+  },
+  "model_type": "my_bert_classifier",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.3"
+}

configuration_my_bert_classifier.py

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+from transformers import PretrainedConfig, BertModel
+
+class MyBertClassifierConfig(PretrainedConfig):
+
+    model_type = "my_bert_classifier"
+
+    def __init__(
+        self,
+        **kwargs,
+    ):
+        
+        super().__init__(**kwargs)

modeling_my_bert_classifier.py

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+from transformers import BertTokenizer, BertModel
+from .configuration_my_bert_classifier import MyBertClassifierConfig
+from torch import nn
+from transformers.modeling_utils import PreTrainedModel
+
+class MyBertClassifier(PreTrainedModel):
+    
+    config_class = MyBertClassifierConfig
+
+    def __init__(self, config):
+
+        super(MyBertClassifier, self).__init__(config)
+
+        self.bert = BertModel.from_pretrained('bert-base-cased')
+        self.dropout = nn.Dropout(0.5)
+        self.linear = nn.Linear(768, 5)
+        self.relu = nn.ReLU()
+
+    def forward(self, input_id, mask):
+
+        _, pooled_output = self.bert(input_ids= input_id, attention_mask=mask,return_dict=False)
+        dropout_output = self.dropout(pooled_output)
+        linear_output = self.linear(dropout_output)
+        final_layer = self.relu(linear_output)
+
+        return final_layer

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:aea6287e038b6df823b11bdebb06b3195bb6cd07b55dae9fc5f2b432bb57093a
+size 433322033