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Albert xxlarge version 1 language model fine-tuned on SQuAD2.0 with the following results:
```
 {'exact': 85.65653162637918,
 'f1': 89.260458954177,
 'total': 11873,
 'HasAns_exact': 82.6417004048583,
 'HasAns_f1': 89.85989020967376,
 'HasAns_total': 5928,
 'NoAns_exact': 88.66274179983179,
 'NoAns_f1': 88.66274179983179,
 'NoAns_total': 5945,
 'best_exact': 85.65653162637918,
 'best_exact_thresh': 0.0,
 'best_f1': 89.2604589541768,
 'best_f1_thresh': 0.0}
```
with script:
```
python -m torch.distributed.launch --nproc_per_node=2 ${RUN_SQUAD_DIR}/run_squad.py \
  --model_type albert \
  --model_name_or_path albert-xxlarge-v1 \
  --do_train \
  --train_file ${SQUAD_DIR}/train-v2.0.json \
  --predict_file ${SQUAD_DIR}/dev-v2.0.json \
  --version_2_with_negative \
  --num_train_epochs 3 \
  --max_steps 8144 \
  --warmup_steps 814 \
  --do_lower_case \
  --learning_rate 3e-5 \
  --max_seq_length 512 \
  --doc_stride 128 \
  --save_steps 2000 \
  --per_gpu_train_batch_size 1 \
  --gradient_accumulation_steps 24 \
  --output_dir ${MODEL_PATH}

CUDA_VISIBLE_DEVICES=0 python ${RUN_SQUAD_DIR}/run_squad.py \
  --model_type albert \
  --model_name_or_path ${MODEL_PATH} \
  --do_eval \
  --train_file ${SQUAD_DIR}/train-v2.0.json \
  --predict_file ${SQUAD_DIR}/dev-v2.0.json \
  --version_2_with_negative \
  --do_lower_case \
  --max_seq_length 512 \
  --per_gpu_eval_batch_size 48 \
  --output_dir ${MODEL_PATH}
```
using the following system & software:
```
OS/Platform: Linux-4.15.0-76-generic-x86_64-with-debian-buster-sid
GPU/CPU: 2 x NVIDIA 1080Ti / Intel i7-8700
Transformers: 2.3.0
PyTorch: 1.4.0
TensorFlow: 2.1.0
Python: 3.7.6
```
Inferencing/prediction works with the current Transformers v2.4.1

Access this `albert_xxlargev1_sqd2_512` fine-tuned model with "tried & true" code:
```
config_class, model_class, tokenizer_class = \
            AlbertConfig, AlbertForQuestionAnswering, AlbertTokenizer

model_name_or_path = "ahotrod/albert_xxlargev1_squad2_512"
config = config_class.from_pretrained(model_name_or_path)
tokenizer = tokenizer_class.from_pretrained(model_name_or_path, do_lower_case=True)
model = model_class.from_pretrained(model_name_or_path, config=config)
```
or the AutoModels (AutoConfig, AutoTokenizer & AutoModel) should also work, however I
have yet to use them in my app & confirm:
```
from transformers import AutoConfig, AutoTokenizer, AutoModel

model_name_or_path = "ahotrod/albert_xxlargev1_squad2_512"
config = AutoConfig.from_pretrained(model_name_or_path)
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, do_lower_case=True)
model = AutoModel.from_pretrained(model_name_or_path, config=config)
```
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2785?src=pr&el=h1) Report
> Merging [#2785](https://codecov.io/gh/huggingface/transformers/pull/2785?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/520e7f211926e07b2059bc8e21b668db4372e4db?src=pr&el=desc) will **not change** coverage.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/2785/graphs/tree.svg?width=650&token=9qOlN6Hb1c&height=150&src=pr)](https://codecov.io/gh/huggingface/transformers/pull/2785?src=pr&el=tree)

```diff
@@           Coverage Diff           @@
##           master    #2785   +/-   ##
=======================================
  Coverage   75.13%   75.13%           
=======================================
  Files          93       93           
  Lines       15249    15249           
=======================================
  Hits        11457    11457           
  Misses       3792     3792
```



------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/2785?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2785?src=pr&el=footer). Last update [520e7f2...48a103f](https://codecov.io/gh/huggingface/transformers/pull/2785?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
<|||||>Just used code fences for consistency with other model cards.

Thanks for sharing!