File size: 742 Bytes
6f5ce92 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | from torch import nn, optim
from transformers import BertModel
# TOKENIZACIÓN
PRE_TRAINED_MODEL_NAME = 'bert-base-cased'
# EL MODELO!
class BERTSentimentClassifier(nn.Module):
def __init__(self, n_classes):
super(BERTSentimentClassifier, self).__init__()
self.bert = BertModel.from_pretrained(PRE_TRAINED_MODEL_NAME)
self.drop = nn.Dropout(p=0.05)
self.linear = nn.Linear(self.bert.config.hidden_size, n_classes)
def forward(self, input_ids, attention_mask):
_, cls_output = self.bert(
input_ids = input_ids,
attention_mask = attention_mask
)
drop_output = self.drop(cls_output)
output = self.linear(drop_output)
return output |