File size: 1,168 Bytes
fdb0b54 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
from transformers import PretrainedConfig, PreTrainedModel, BertModel, BertConfig
from torch import nn
class SimBertModel(PreTrainedModel):
""" SimBert Model
"""
config_class = BertConfig
def __init__(
self,
config: PretrainedConfig
) -> None:
super().__init__(config)
self.bert = BertModel(config=config, add_pooling_layer=True)
self.fc = nn.Linear(config.hidden_size, 2)
# self.loss_fct = nn.CrossEntropyLoss()
self.loss_fct = nn.MSELoss()
self.softmax = nn.Softmax(dim=1)
def forward(
self,
input_ids,
token_type_ids,
attention_mask,
labels=None
):
outputs = self.bert(
input_ids=input_ids,
attention_mask=attention_mask,
token_type_ids=token_type_ids
)
pooled_output = outputs.pooler_output
logits = self.fc(pooled_output)
logits = self.softmax(logits)[:,1]
if labels is not None:
loss = self.loss_fct(logits.view(-1), labels.view(-1))
return loss, logits
return None, logits |