Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#6)

- Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (a4cf1204a176000962759b937e88cff97f187d16)


Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>

.gitattributes

@@ -6,3 +6,4 @@
 *.tar.gz filter=lfs diff=lfs merge=lfs -text
 *.ot filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,97 @@
+---
+language: en
+license: cc-by-4.0
+datasets:
+- squad_v2
+model-index:
+- name: deepset/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
+---
+
+# 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="deepset/bert-large-uncased-whole-word-masking-squad2")
+# or 
+reader = TransformersReader(model_name_or_path="FILL",tokenizer="deepset/bert-large-uncased-whole-word-masking-squad2")
+```
+
+### In Transformers
+```python
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+
+model_name = "deepset/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)

config.json

@@ -3,45 +3,21 @@
     "BertForQuestionAnswering"
   ],
   "attention_probs_dropout_prob": 0.1,
-  "do_sample": false,
   "finetuning_task": "squad2",
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 1024,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1"
-  },
   "initializer_range": 0.02,
   "intermediate_size": 4096,
-  "is_decoder": false,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1
-  },
   "language": "english",
   "layer_norm_eps": 1e-12,
-  "length_penalty": 1.0,
-  "max_length": 20,
   "max_position_embeddings": 512,
   "model_type": "bert",
   "name": "Bert",
   "num_attention_heads": 16,
-  "num_beams": 1,
   "num_hidden_layers": 24,
-  "num_labels": 2,
-  "num_return_sequences": 1,
-  "output_attentions": false,
-  "output_hidden_states": false,
   "output_past": true,
   "pad_token_id": 0,
-  "pruned_heads": {},
-  "repetition_penalty": 1.0,
-  "temperature": 1.0,
-  "top_k": 50,
-  "top_p": 1.0,
-  "torchscript": false,
   "type_vocab_size": 2,
-  "use_bfloat16": false,
   "vocab_size": 30522
 }

modelcard.json

@@ -1,11 +0,0 @@
-{
-  "caveats_and_recommendations": {},
-  "ethical_considerations": {},
-  "evaluation_data": {},
-  "factors": {},
-  "intended_use": {},
-  "metrics": {},
-  "model_details": {},
-  "quantitative_analyses": {},
-  "training_data": {}
-}