ValueError: too many dimensions 'str'
# 🐛 Bug

**To Reproduce**
Steps to reproduce the behavior:

Here is my Colab Notebook you can run to to see the error
https://colab.research.google.com/drive/1ESyf46RNBvrg-7DDQ5l8zhlKZjWGdqUv#scrollTo=MqlsdjFVMmMZ

```
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-9-0b9dcdf94c77> in <module>()
     71 
     72 # Train the model
---> 73 model.train_model(train_df)
     74 
     75 # Evaluate the model

1 frames
/usr/local/lib/python3.6/dist-packages/simpletransformers/classification/classification_model.py in train_model(self, train_df, multi_label, output_dir, show_running_loss, args, eval_df, verbose, **kwargs)
    261             ]
    262 
--> 263         train_dataset = self.load_and_cache_examples(train_examples, verbose=verbose)
    264 
    265         os.makedirs(output_dir, exist_ok=True)

/usr/local/lib/python3.6/dist-packages/simpletransformers/classification/classification_model.py in load_and_cache_examples(self, examples, evaluate, no_cache, multi_label, verbose, silent)
    757 
    758         if output_mode == "classification":
--> 759             all_label_ids = torch.tensor([f.label_id for f in features], dtype=torch.long)
    760         elif output_mode == "regression":
    761             all_label_ids = torch.tensor([f.label_id for f in features], dtype=torch.float)

ValueError: too many dimensions 'str'

```

The problem arises when using

```
from simpletransformers.classification import ClassificationModel

import pandas as pd
prefix = '/content/'
train_df = pd.read_csv(prefix + 'train.csv', header=None)
train_df=train_df.drop(index=0)

model = ClassificationModel('roberta', 'roberta-base')

model.train_model(train_df)

```


I suggest to close this topic and keep the discussion over at https://github.com/ThilinaRajapakse/simpletransformers/issues/229.