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README.md

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 ---
-license: apache-2.0
+language: en
+license: cc-by-4.0
+datasets:
+- squad_v2
+model-index:
+- name: vicky4s4s/deepsets-bert-large-uncased-whole-word-masking-squad2
+  results:
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squad_v2
+      type: squad_v2
+      config: squad_v2
+      split: validation
+    metrics:
+    - type: exact_match
+      value: 80.8846
+      name: Exact Match
+      verified: true
+      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2E5ZGNkY2ExZWViZGEwNWE3OGRmMWM2ZmE4ZDU4ZDQ1OGM3ZWE0NTVmZjFmYmZjZmJmNjJmYTc3NTM3OTk3OSIsInZlcnNpb24iOjF9.aSblF4ywh1fnHHrN6UGL392R5KLaH3FCKQlpiXo_EdQ4XXEAENUCjYm9HWDiFsgfSENL35GkbSyz_GAhnefsAQ
+    - type: f1
+      value: 83.8765
+      name: F1
+      verified: true
+      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGFlNmEzMTk2NjRkNTI3ZTk3ZTU1NWNlYzIyN2E0ZDFlNDA2ZjYwZWJlNThkMmRmMmE0YzcwYjIyZDM5NmRiMCIsInZlcnNpb24iOjF9.-rc2_Bsp_B26-o12MFYuAU0Ad2Hg9PDx7Preuk27WlhYJDeKeEr32CW8LLANQABR3Mhw2x8uTYkEUrSDMxxLBw
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squad
+      type: squad
+      config: plain_text
+      split: validation
+    metrics:
+    - type: exact_match
+      value: 85.904
+      name: Exact Match
+    - type: f1
+      value: 92.586
+      name: F1
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: adversarial_qa
+      type: adversarial_qa
+      config: adversarialQA
+      split: validation
+    metrics:
+    - type: exact_match
+      value: 28.233
+      name: Exact Match
+    - type: f1
+      value: 41.170
+      name: F1
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squad_adversarial
+      type: squad_adversarial
+      config: AddOneSent
+      split: validation
+    metrics:
+    - type: exact_match
+      value: 78.064
+      name: Exact Match
+    - type: f1
+      value: 83.591
+      name: F1
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squadshifts amazon
+      type: squadshifts
+      config: amazon
+      split: test
+    metrics:
+    - type: exact_match
+      value: 65.615
+      name: Exact Match
+    - type: f1
+      value: 80.733
+      name: F1
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squadshifts new_wiki
+      type: squadshifts
+      config: new_wiki
+      split: test
+    metrics:
+    - type: exact_match
+      value: 81.570
+      name: Exact Match
+    - type: f1
+      value: 91.199
+      name: F1
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squadshifts nyt
+      type: squadshifts
+      config: nyt
+      split: test
+    metrics:
+    - type: exact_match
+      value: 83.279
+      name: Exact Match
+    - type: f1
+      value: 91.090
+      name: F1
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: squadshifts reddit
+      type: squadshifts
+      config: reddit
+      split: test
+    metrics:
+    - type: exact_match
+      value: 69.305
+      name: Exact Match
+    - type: f1
+      value: 82.405
+      name: F1
 ---
+
+# bert-large-uncased-whole-word-masking-squad2
+
+This is a berta-large model, fine-tuned using the SQuAD2.0 dataset for the task of question answering.
+
+## Overview
+**Language model:** bert-large  
+**Language:** English  
+**Downstream-task:** Extractive QA  
+**Training data:** SQuAD 2.0  
+**Eval data:** SQuAD 2.0  
+**Code:**  See [an example QA pipeline on Haystack](https://haystack.deepset.ai/tutorials/first-qa-system)  
+
+## Usage
+
+### In Haystack
+Haystack is an NLP framework by deepset. You can use this model in a Haystack pipeline to do question answering at scale (over many documents). To load the model in [Haystack](https://github.com/deepset-ai/haystack/):
+```python
+reader = FARMReader(model_name_or_path="vicky4s4s/deepsets-bert-large-uncased-whole-word-masking-squad2")
+# or 
+reader = TransformersReader(model_name_or_path="FILL",tokenizer="vicky4s4s/deepsets-bert-large-uncased-whole-word-masking-squad2")
+```
+
+### In Transformers
+```python
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+
+model_name = "vicky4s4s/deepsets-bert-large-uncased-whole-word-masking-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)
+```
+
+## About us
+<div class="grid lg:grid-cols-2 gap-x-4 gap-y-3">
+    <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
+         <img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/deepset-logo-colored.png" class="w-40"/>
+     </div>
+     <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
+         <img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/haystack-logo-colored.png" class="w-40"/>
+     </div>
+</div>
+
+[deepset](http://deepset.ai/) is the company behind the open-source NLP framework [Haystack](https://haystack.deepset.ai/) which is designed to help you build production ready NLP systems that use: Question answering, summarization, ranking etc.
+
+
+Some of our other work: 
+- [Distilled roberta-base-squad2 (aka "tinyroberta-squad2")]([https://huggingface.co/deepset/tinyroberta-squad2)
+- [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
+- [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
+
+## Get in touch and join the Haystack community
+
+<p>For more info on Haystack, visit our <strong><a href="https://github.com/deepset-ai/haystack">GitHub</a></strong> repo and <strong><a href="https://docs.haystack.deepset.ai">Documentation</a></strong>. 
+
+We also have a <strong><a class="h-7" href="https://haystack.deepset.ai/community">Discord community open to everyone!</a></strong></p>
+
+[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Discord](https://haystack.deepset.ai/community/join) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)
+
+By the way: [we're hiring!](http://www.deepset.ai/jobs)

added_tokens.json

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+{}

config.json

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+{
+  "architectures": [
+    "BertForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "finetuning_task": "squad2",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "language": "english",
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "name": "Bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "type_vocab_size": 2,
+  "vocab_size": 30522
+}

model.safetensors

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special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"init_inputs": []}