NER training crash
transformers version: 4.17.0

Hi, I run the script for NER task for [few-nerd](https://huggingface.co/datasets/dfki-nlp/few-nerd) dataset
https://github.com/huggingface/transformers/blob/main/examples/pytorch/token-classification/run_ner_no_trainer.py


```
 CUDA_VISIBLE_DEVICES=3  python -u run_ner_no_trainer.py \
  --model_name_or_path roberta-large \
  --dataset_name dfki-nlp/few-nerd \
  --dataset_config_name "supervised" \
  --output_dir /scratch/w/wluyliu/yananc/finetunes/roberta_nerd_fine \
  --text_column_name "tokens" \
  --label_column_name "fine_ner_tags" \
  --num_train_epochs 7  --local_files_only --debug  --debug_cnt 50000
```
When I use small samples, for example below 30000, things go smoothly and the precision, recall and F1 are in good alignment with the original paper.

However, when I increase the samples used for training, for example, 50000, or full set, the metrics become zero, where the predictions from model are all "O".  It is quite weird. 

I also try the conll2003 dataset, it is the same. 

Am I miss something ?

Thanks.


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/main/CONTRIBUTING.md) are likely to be ignored.<|||||>Was that issue resolved? I am facing a similar problem with the HF implementation of LUKE: https://github.com/huggingface/transformers/tree/main/examples/research_projects/luke