Hello, I’m working on the classification task of 8 classes using bert model, but I keep getting this error of ‘index out of range’
Your help, please.
Thanks
for e in range(epochs):
print('Training...')
# Reset the total loss for this epoch.
total_loss = 0
for batch in train_dataloader:
batch = [b.to(device) for b in batch]
sent_id, mask, labels = batch
# Clear out the gradients
model.zero_grad()
#Forwad pass
output = model(sent_id, mask, labels)
IndexError Traceback (most recent call last)
in
26
27 #Forwad pass
---> 28 output = model(sent_id, mask, labels)
29
30 loss, _ = output
C:\python\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
C:\python\envs\pytorch\lib\site-packages\transformers\modeling_bert.py in forward(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, labels, output_attentions, output_hidden_states)
1265 inputs_embeds=inputs_embeds,
1266 output_attentions=output_attentions,
-> 1267 output_hidden_states=output_hidden_states,
1268 )
1269
C:\python\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
C:\python\envs\pytorch\lib\site-packages\transformers\modeling_bert.py in forward(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, encoder_hidden_states, encoder_attention_mask, output_attentions, output_hidden_states)
751
752 embedding_output = self.embeddings(
--> 753 input_ids=input_ids, position_ids=position_ids, token_type_ids=token_type_ids, inputs_embeds=inputs_embeds
754 )
755 encoder_outputs = self.encoder(
C:\python\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
C:\python\envs\pytorch\lib\site-packages\transformers\modeling_bert.py in forward(self, input_ids, token_type_ids, position_ids, inputs_embeds)
178 inputs_embeds = self.word_embeddings(input_ids)
179 position_embeddings = self.position_embeddings(position_ids)
--> 180 token_type_embeddings = self.token_type_embeddings(token_type_ids)
181
182 embeddings = inputs_embeds + position_embeddings + token_type_embeddings
C:\python\envs\pytorch\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
720 result = self._slow_forward(*input, **kwargs)
721 else:
--> 722 result = self.forward(*input, **kwargs)
723 for hook in itertools.chain(
724 _global_forward_hooks.values(),
C:\python\envs\pytorch\lib\site-packages\torch\nn\modules\sparse.py in forward(self, input)
124 return F.embedding(
125 input, self.weight, self.padding_idx, self.max_norm,
--> 126 self.norm_type, self.scale_grad_by_freq, self.sparse)
127
128 def extra_repr(self) -> str:
C:\python\envs\pytorch\lib\site-packages\torch\nn\functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
1812 # remove once script supports set_grad_enabled
1813 _no_grad_embedding_renorm_(weight, input, max_norm, norm_type)
-> 1814 return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
1815
1816
IndexError: index out of range in self