From fc2657c72c311728997848d732c30c143b0c54a9 Mon Sep 17 00:00:00 2001
From: Julien Chaumond <julien@huggingface.co>
Date: Fri, 11 Dec 2020 22:38:04 +0100
Subject: [PATCH] Migrate model card from transformers-repo

Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/deepset/minilm-uncased-squad2/README.md
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+---
+datasets:
+- squad_v2
+---
+
+# MiniLM-L12-H384-uncased for QA
+
+## Overview
+**Language model:** microsoft/MiniLM-L12-H384-uncased
+**Language:** English
+**Downstream-task:** Extractive QA
+**Training data:** SQuAD 2.0
+**Eval data:** SQuAD 2.0
+**Code:**  See [example](https://github.com/deepset-ai/FARM/blob/master/examples/question_answering.py) in [FARM](https://github.com/deepset-ai/FARM/blob/master/examples/question_answering.py)
+**Infrastructure**: 1x Tesla v100
+
+## Hyperparameters
+
+```
+seed=42
+batch_size = 12
+n_epochs = 4
+base_LM_model = "microsoft/MiniLM-L12-H384-uncased"
+max_seq_len = 384
+learning_rate = 4e-5
+lr_schedule = LinearWarmup
+warmup_proportion = 0.2
+doc_stride=128
+max_query_length=64
+grad_acc_steps=4
+```
+
+## Performance
+Evaluated on the SQuAD 2.0 dev set with the [official eval script](https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/).
+```
+"exact": 76.13071675229513,
+"f1": 79.49786500219953,
+"total": 11873,
+"HasAns_exact": 78.35695006747639,
+"HasAns_f1": 85.10090269418276,
+"HasAns_total": 5928,
+"NoAns_exact": 73.91084945332211,
+"NoAns_f1": 73.91084945332211,
+"NoAns_total": 5945
+```
+
+## Usage
+
+### In Transformers
+```python
+from transformers import AutoModelForQuestionAnswering,  AutoTokenizer, pipeline
+
+model_name = "deepset/minilm-uncased-squad2"
+
+# a) Get predictions
+nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+QA_input = {
+    'question': 'Why is model conversion important?',
+    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
+}
+res = nlp(QA_input)
+
+# b) Load model & tokenizer
+model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+```
+
+### In FARM
+
+```python
+from farm.modeling.adaptive_model import AdaptiveModel
+from farm.modeling.tokenization import Tokenizer
+from farm.infer import Inferencer
+
+model_name = "deepset/minilm-uncased-squad2"
+
+# a) Get predictions
+nlp = Inferencer.load(model_name, task_type="question_answering")
+QA_input = [{"questions": ["Why is model conversion important?"],
+             "text": "The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks."}]
+res = nlp.inference_from_dicts(dicts=QA_input)
+
+# b) Load model & tokenizer
+model = AdaptiveModel.convert_from_transformers(model_name, device="cpu", task_type="question_answering")
+tokenizer = Tokenizer.load(model_name)
+```
+
+### In haystack
+For doing QA at scale (i.e. many docs instead of single paragraph), you can load the model also in [haystack](https://github.com/deepset-ai/haystack/):
+```python
+reader = FARMReader(model_name_or_path="deepset/minilm-uncased-squad2")
+# or
+reader = TransformersReader(model="deepset/minilm-uncased-squad2",tokenizer="deepset/minilm-uncased-squad2")
+```
+
+
+## Authors
+Vaishali Pal `vaishali.pal [at] deepset.ai`
+Branden Chan: `branden.chan [at] deepset.ai`
+Timo Möller: `timo.moeller [at] deepset.ai`
+Malte Pietsch: `malte.pietsch [at] deepset.ai`
+Tanay Soni: `tanay.soni [at] deepset.ai`
+
+## About us
+![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png)
+
+We bring NLP to the industry via open source!
+Our focus: Industry specific language models & large scale QA systems.
+
+Some of our work:
+- [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
+- [FARM](https://github.com/deepset-ai/FARM)
+- [Haystack](https://github.com/deepset-ai/haystack/)
+
+Get in touch:
+[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Website](https://deepset.ai)