l3c_hindi-bert-scratch_error.dump

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
/tmp/ipykernel_17/2958370653.py in <module>
      1 for DATASET in POSSIBLE_DATASETS:
      2     for MODEL_ALIAS in POSSIBLE_MODEL_ALIASES:
----> 3         train_eval_test(MODEL_ALIAS, DATASET)

/tmp/ipykernel_17/1094019785.py in train_eval_test(MODEL_ALIAS, DATASET)
     35         model.train()
     36         for batch in train_dl:
---> 37             outputs = model(batch)
     38 
     39             loss = loss_fn(outputs, batch[1].to(device))

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1108         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1109                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110             return forward_call(*input, **kwargs)
   1111         # Do not call functions when jit is used
   1112         full_backward_hooks, non_full_backward_hooks = [], []

/tmp/ipykernel_17/3524776035.py in forward(self, batch)
     21             k: v.to(self.device) for k, v in tokenized.items()
     22         }
---> 23         x = self.backbone(**tokenized)
     24         x = self.lin(x.pooler_output)
     25         return x

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1108         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1109                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110             return forward_call(*input, **kwargs)
   1111         # Do not call functions when jit is used
   1112         full_backward_hooks, non_full_backward_hooks = [], []

/opt/conda/lib/python3.7/site-packages/transformers/models/bert/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, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)
   1014             token_type_ids=token_type_ids,
   1015             inputs_embeds=inputs_embeds,
-> 1016             past_key_values_length=past_key_values_length,
   1017         )
   1018         encoder_outputs = self.encoder(

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1108         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1109                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110             return forward_call(*input, **kwargs)
   1111         # Do not call functions when jit is used
   1112         full_backward_hooks, non_full_backward_hooks = [], []

/opt/conda/lib/python3.7/site-packages/transformers/models/bert/modeling_bert.py in forward(self, input_ids, token_type_ids, position_ids, inputs_embeds, past_key_values_length)
    233 
    234         if inputs_embeds is None:
--> 235             inputs_embeds = self.word_embeddings(input_ids)
    236         token_type_embeddings = self.token_type_embeddings(token_type_ids)
    237 

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1108         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1109                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110             return forward_call(*input, **kwargs)
   1111         # Do not call functions when jit is used
   1112         full_backward_hooks, non_full_backward_hooks = [], []

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/sparse.py in forward(self, input)
    158         return F.embedding(
    159             input, self.weight, self.padding_idx, self.max_norm,
--> 160             self.norm_type, self.scale_grad_by_freq, self.sparse)
    161 
    162     def extra_repr(self) -> str:

/opt/conda/lib/python3.7/site-packages/torch/nn/functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
   2181         # remove once script supports set_grad_enabled
   2182         _no_grad_embedding_renorm_(weight, input, max_norm, norm_type)
-> 2183     return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
   2184 
   2185 

IndexError: index out of range in self