model.py

from transformers import BertModel
import torch.nn as nn
import torch.nn.functional as F

class SentimentModel(nn.Module):

    def __init__(self, config):
        super(SentimentModel, self).__init__()
        self.bert = BertModel.from_pretrained(modelName, return_dict=False)
        self.dropout = nn.Dropout(0.3)
        self.classifier = nn.Linear(config.hidden_size, config.num_labels)
    
    def forward(self, input_ids, attention_mask):
        _, pooled_output = self.bert(
            input_ids=input_ids, 
            attention_mask=attention_mask)
        pooled_output = self.dropout(pooled_output)
        logits = self.classifier(pooled_output)
        return logits