Bert Uncased Large giving very low results with SQUAD v1.1 dataset
**Configuration:**
- do_lower_case=True
- max_answer_length=30
- max_answer_length=30
- n_best_size=20
- verbose_logging=False
- bert_model="bert-large-uncased"
- max_seq_length=384
- doc_stride=128
- max_query_length=192
- local_rank=-1
- train_batch_size=12
- predict_batch_size=12
- num_train_epochs=2.0
- gradient_accumulation_steps=1
- fp16=True
- warmup_proportion=0.1
- learning_rate=3e-5

**Results:**
1. Getting very bad results with the given configuration.
2. Kindly let me know if there is an issue with the configuration.
3. Getting many repeated terms for different questions under the same context

[dev1.1_squad_best_results.txt](https://github.com/huggingface/pytorch-pretrained-BERT/files/2935422/dev1.1_squad_best_results.txt)
Sample Dev1.1 Squad(First 9 Questions from development dataset):
    "56be4db0acb8001400a502ec": "Levi's Stadium in the San Francisco Bay Area at Santa Clara,",
    "56be4db0acb8001400a502ed": "Levi's Stadium in the San Francisco Bay Area at Santa Clara,",
    "56be4db0acb8001400a502ee": "Levi's",
    "56be4db0acb8001400a502ef": "Levi's",
    "56be4db0acb8001400a502f0": "Levi's Stadium in the San Francisco Bay Area at Santa Clara,",
    "56be8e613aeaaa14008c90d1": "7",
    "56be8e613aeaaa14008c90d2": "Levi's",
    "56be8e613aeaaa14008c90d3": "7, 2016, at Levi's",
    "56bea9923aeaaa14008c91b9": "7",

Looking forward for the help.
Thanks