found an item of type float at index (0)

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-37-16682764c468> in <module>()
----> 1 fit(m, md, 1, lo.opt, F.binary_cross_entropy)
      2 # use F.binary_cross_entropy for multi-label problems

~\Dropbox\3.SelfStudy\fastai_pytorch\fastai\courses\dl1\fastai\model.py in fit(model, data, epochs, opt, crit, metrics, callbacks, **kwargs)
    104             i += 1
    105 
--> 106         vals = validate(stepper, data.val_dl, metrics)
    107         if epoch == 0: print(layout.format(*names))
    108         print_stats(epoch, [debias_loss] + vals)

~\Dropbox\3.SelfStudy\fastai_pytorch\fastai\courses\dl1\fastai\model.py in validate(stepper, dl, metrics)
    123     loss,res = [],[]
    124     stepper.reset(False)
--> 125     for (*x,y) in iter(dl):
    126         preds,l = stepper.evaluate(VV(x), VV(y))
    127         loss.append(to_np(l))

~\Dropbox\3.SelfStudy\fastai_pytorch\fastai\courses\dl1\fastai\dataset.py in __next__(self)
    241         if self.i>=len(self.dl): raise StopIteration
    242         self.i+=1
--> 243         return next(self.it)
    244 
    245     @property

<ipython-input-20-c08f5408c833> in __iter__(self)
     49         it = iter(self.src)
     50         for i in range(len(self)):
---> 51             b = next(it)
     52 
     53             if (len(self.y_flds) > 1):

~\Dropbox\3.SelfStudy\ml_lab\Anaconda3\envs\fastai\lib\site-packages\torchtext\data\iterator.py in __iter__(self)
    178                         minibatch.sort(key=self.sort_key, reverse=True)
    179                 yield Batch(minibatch, self.dataset, self.device,
--> 180                             self.train)
    181             if not self.repeat:
    182                 raise StopIteration

~\Dropbox\3.SelfStudy\ml_lab\Anaconda3\envs\fastai\lib\site-packages\torchtext\data\batch.py in __init__(self, data, dataset, device, train)
     20                 if field is not None:
     21                     batch = [x.__dict__[name] for x in data]
---> 22                     setattr(self, name, field.process(batch, device=device, train=train))
     23 
     24     @classmethod

~\Dropbox\3.SelfStudy\ml_lab\Anaconda3\envs\fastai\lib\site-packages\torchtext\data\field.py in process(self, batch, device, train)
    185         """
    186         padded = self.pad(batch)
--> 187         tensor = self.numericalize(padded, device=device, train=train)
    188         return tensor
    189 

~\Dropbox\3.SelfStudy\ml_lab\Anaconda3\envs\fastai\lib\site-packages\torchtext\data\field.py in numericalize(self, arr, device, train)
    307                 arr = self.postprocessing(arr, None, train)
    308 
--> 309         arr = self.tensor_type(arr)
    310         if self.sequential and not self.batch_first:
    311             arr.t_()

RuntimeError: tried to construct a tensor from a int sequence, but found an item of type float at index (0)

Update on the issue. A probable solution as mentioned by a commenter here (facebookresearch/InferSent#2)

When you define a Field in torchtext by default it is torch.LongTensor , so you can pass whatever type you want like this data.Field(sequential=False, use_vocab=False,tensor_type=torch.cuda.FloatTensor)

So happens when I changed my code accordingly as per his suggestion (below), the error no longer appears.
tt_TEXT = data.Field(sequential=True, tokenize=tokenizer, fix_length=max_len)
tt_LABEL = data.Field(sequential=False, use_vocab=False,tensor_type=torch.cuda.FloatTensor)