pytorch jax bert text-classification transformers
.gitattributes README.md config.json flax_model.msgpack pytorch_model.bin special_tokens_map.json tokenizer_config.json trainer_state.json training_args.bin vocab.txt
## BERT-large finetuned on MNLI.

The [reference finetuned model](https://github.com/google-research/bert) has an accuracy of 86.05, we get 86.7:

```
{'eval_loss': 0.3984006643295288, 'eval_accuracy': 0.8667345899133979} 
```