Hello @ptrblck, Thankyou for responding.
I have tried using your snippet.
I don’t think its a data issue as I have changes seeds and  split_ratio.
Always, the error is in the validation set.
If there had been an issue in data then I guess train_iterator would also throw an error but train_iterator runs perfectly well.
Full Code Snippet for your reference:
TEXT = data.Field(tokenize='spacy',batch_first=True,include_lengths=True)
LABEL = data.LabelField(dtype = torch.float,batch_first=True)

fields = [('question_text',TEXT),('target', LABEL)]
training_data=data.TabularDataset(path = 'quora.csv',format = 'csv',fields = fields,skip_header = True)

SEED = 20
train_data, valid_data = training_data.split(split_ratio=0.7, random_state = random.seed(SEED))

TEXT.build_vocab(train_data,min_freq=3,vectors = "glove.6B.100d")  
LABEL.build_vocab(train_data)

#set batch size
BATCH_SIZE = 64

#Load an iterator
train_iterator, valid_iterator = data.BucketIterator.splits(
    (train_data, valid_data), 
    batch_size = BATCH_SIZE,
    sort_key = lambda x: len(x.question_text),
    sort_within_batch=True,sort=False)

for idx, batch in enumerate(valid_iterator):
    print(idx)
    text, text_lengths = batch.question_text