[s2s examples] Replace -100 token ids with the tokenizer pad_id for compute_metrics
# What does this PR do?

This PR is a small fix that replaces the -100 token ids with the tokenizer pad_id when decoding sequences to compute metrics as was done in [this HF blog post](https://huggingface.co/blog/warm-starting-encoder-decoder)

## When does this problem occur?

When running `examples/seq2seq/finetune_trainer.py` with padding to the `max_seq_len`, an error is thrown at the evaluation step:

```
  File "/opt/conda/lib/python3.8/site-packages/transformers/trainer.py", line 1004, in _maybe_log_save_evaluate
    metrics = self.evaluate()
  File "/opt/conda/lib/python3.8/site-packages/transformers/trainer_seq2seq.py", line 96, in evaluate
    return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
  File "/opt/conda/lib/python3.8/site-packages/transformers/trainer.py", line 1442, in evaluate
    output = self.prediction_loop(
  File "/opt/conda/lib/python3.8/site-packages/transformers/trainer.py", line 1601, in prediction_loop
    metrics = self.compute_metrics(EvalPrediction(predictions=preds, label_ids=label_ids))
  File "/eai/transformers/examples/seq2seq/utils.py", line 98, in translation_metrics
    pred_str, label_str = decode_pred(pred)
  File "/eai/transformers/examples/seq2seq/utils.py", line 85, in decode_pred
    label_str = tokenizer.batch_decode(pred.label_ids, skip_special_tokens=True)
  File "/opt/conda/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 3070, in batch_decode
    return [
  File "/opt/conda/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 3071, in <listcomp>
    self.decode(
  File "/opt/conda/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 3109, in decode
    return self._decode(
  File "/opt/conda/lib/python3.8/site-packages/transformers/tokenization_utils_fast.py", line 495, in _decode
    text = self._tokenizer.decode(token_ids, skip_special_tokens=skip_special_tokens)
OverflowError: out of range integral type conversion attempted
```

This is because in the prediction loop, the labels will be padded with -100 if the prediction or labels have different sequence length https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py#L1637.


Hi, 
Still running into this issue here with the run_summarization.py file - 


```Traceback (most recent call last):
  File "run_summarization.py", line 674, in <module>
    main()
  File "run_summarization.py", line 628, in main
    predict_results = trainer.predict(
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/trainer_seq2seq.py", line 125, in predict
    return super().predict(test_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/trainer.py", line 2133, in predict
    output = eval_loop(
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/trainer.py", line 2235, in evaluation_loop
    loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/trainer_seq2seq.py", line 180, in prediction_step
    print(self.tokenizer_t5.batch_decode(inputs["labels"], skip_special_tokens=True, clean_up_tokenization_spaces=True))
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/tokenization_utils_base.py", line 3047, in batch_decode
    return [
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/tokenization_utils_base.py", line 3048, in <listcomp>
    self.decode(
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/tokenization_utils_base.py", line 3086, in decode
    return self._decode(
  File "/Users/aiswarya.s/Desktop/transformers_fudge/src/transformers/tokenization_utils_fast.py", line 507, in _decode
    text = self._tokenizer.decode(token_ids, skip_special_tokens=skip_special_tokens)
OverflowError: out of range integral type conversion attempted```

Has this been addressed in that script - it relies on the trainer_seq2seq.py file, not sure if this issue has been fixed there.  Thanks cc @patil-suraj 

