Different evaluation results 
Author: midannii
Pull request: no

## Environment info

- `transformers` version: 4.10.0
- Platform: Linux-4.15.0-142-generic-x86_64-with-debian-stretch-sid
- Python version: 3.7.11
- PyTorch version (GPU?): 1.10.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>

### Who can help

 --> @patrickvonplaten,  @sgugger, @patil-suraj

## Information

Model I am using (Bert, XLNet ...):

The problem arises when using:
* [ ㅇ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ㅇ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. download transformer with `git clone`
2. move to ~/transformers/examples/pytorch/question-answering
3. run example code with below code
4. 
```
python run_qa.py   --model_name_or_path bert-base-uncased   --dataset_name squad   --do_train   --do_eval   --per_device_train_batch_size 12   --learning_rate 3e-5   --num_train_epochs 2   --max_seq_length 384   --doc_stride 128   --output_dir /tmp/debug_squad/
```


## Expected behavior

1. My result indicates the results below 

```
***** eval metrics *****
  epoch            =     2.0
  eval_exact_match = 79.8108
  eval_f1          = 87.5898
  eval_samples     =   10784
```

but, as mentioned at `README.md` of question-answering, expected result is `f1 = 88.52  \  exact_match = 81.22`

I want to know why there is a difference between them. 



2. When I run 

```
python run_qa.py   --model_name_or_path bert-base-uncased   --dataset_name squad   --do_train   --do_eval   --per_device_train_batch_size 12   --learning_rate 3e-5   --num_train_epochs 2   --max_seq_length 384   --doc_stride 128   --output_dir /tmp/debug_squad/
```

I face the message, ` [INFO|trainer.py:521] 2021-12-27 20:42:58,092 >> The following columns in the evaluation set  don't have a corresponding argument in `BertForQuestionAnswering.forward` and have been ignored: example_id, offset_mapping.`. 


I want to run `BertForQuestionAnswering.forward` but I don't know how to. ;<






Comments:
I'm not entirely sure the result section is up to date, so it may have been with slightly different hyperparameters (like a batch size of 8 which is the default). It might also be an error in the base checkpoint used, as I may have used the `bert-base-cased` checkpoint to get those results.

For your second question, this log is completely normal. If you look at the script, it processes the dataset and there will be in it columns the model expects and two it does not, which are dropped when running evaluation.

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.