updated

README.md

@@ -1,242 +0,0 @@
----
-language: en
-license: cc-by-4.0
-tags:
-- deberta
-- deberta-v3
-- deberta-v3-large
-datasets:
-- squad_v2
-model-index:
-- name: deepset/deberta-v3-large-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: 88.0876
-      name: Exact Match
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmE0MWEwNjBkNTA1MmU0ZDkyYTA1OGEwNzY3NGE4NWU4NGI0NTQzNjRlNjY1NGRmNDU2MjA0NjU1N2JlZmNhYiIsInZlcnNpb24iOjF9.PnBF_vD0HujNBSShGJzsJnjmiBP_qT8xb2E7ORmpKfNspKXEuN_pBk9iV0IHRzdqOSyllcxlCv93XMPblNjWDw
-    - type: f1
-      value: 91.1623
-      name: F1
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDBkNDUzZmNkNDQwOGRkMmVlZjkxZWVlMzk3NzFmMGIxMTFmMjZlZDcyOWFiMjljNjM5MThlZDM4OWRmNzMwOCIsInZlcnNpb24iOjF9.bacyetziNI2DxO67GWpTyeRPXqF1POkyv00wEHXlyZu71pZngsNpZyrnuj2aJlCqQwHGnF_lT2ysaXKHprQRBg
-  - task:
-      type: question-answering
-      name: Question Answering
-    dataset:
-      name: squad
-      type: squad
-      config: plain_text
-      split: validation
-    metrics:
-    - type: exact_match
-      value: 89.2366
-      name: Exact Match
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjQ1Yjk3YTdiYTY1NmYxMTI1ZGZlMjRkNTlhZTkyNjRkNjgxYWJiNDk2NzE3NjAyYmY3YmRjNjg4YmEyNDkyYyIsInZlcnNpb24iOjF9.SEWyqX_FPQJOJt2KjOCNgQ2giyVeLj5bmLI5LT_Pfo33tbWPWD09TySYdsthaVTjUGT5DvDzQLASSwBH05FyBw
-    - type: f1
-      value: 95.0569
-      name: F1
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2QyODQ1NWVlYjQxMjA0YTgyNmQ2NmIxOWY3MDRmZjE3ZWI5Yjc4ZDE4NzA2YjE2YTE1YTBlNzNiYmNmNzI3NCIsInZlcnNpb24iOjF9.NcXEc9xoggV76w1bQKxuJDYbOTxFzdny2k-85_b6AIMtfpYV3rGR1Z5YF6tVY2jyp7mgm5Jd5YSgGI3NvNE-CQ
-  - task:
-      type: question-answering
-      name: Question Answering
-    dataset:
-      name: adversarial_qa
-      type: adversarial_qa
-      config: adversarialQA
-      split: validation
-    metrics:
-    - type: exact_match
-      value: 42.100
-      name: Exact Match
-    - type: f1
-      value: 56.587
-      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: 83.548
-      name: Exact Match
-    - type: f1
-      value: 89.385
-      name: F1
-  - task:
-      type: question-answering
-      name: Question Answering
-    dataset:
-      name: squadshifts amazon
-      type: squadshifts
-      config: amazon
-      split: test
-    metrics:
-    - type: exact_match
-      value: 72.979
-      name: Exact Match
-    - type: f1
-      value: 87.254
-      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: 83.938
-      name: Exact Match
-    - type: f1
-      value: 92.695
-      name: F1
-  - task:
-      type: question-answering
-      name: Question Answering
-    dataset:
-      name: squadshifts nyt
-      type: squadshifts
-      config: nyt
-      split: test
-    metrics:
-    - type: exact_match
-      value: 85.534
-      name: Exact Match
-    - type: f1
-      value: 93.153
-      name: F1
-  - task:
-      type: question-answering
-      name: Question Answering
-    dataset:
-      name: squadshifts reddit
-      type: squadshifts
-      config: reddit
-      split: test
-    metrics:
-    - type: exact_match
-      value: 73.284
-      name: Exact Match
-    - type: f1
-      value: 85.307
-      name: F1
----
-# deberta-v3-large for QA 
-
-This is the [deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) model, fine-tuned using the [SQuAD2.0](https://huggingface.co/datasets/squad_v2) dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering. 
-
-
-## Overview
-**Language model:** deberta-v3-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)  
-**Infrastructure**: 1x NVIDIA A10G
-
-## Hyperparameters
-
-```
-batch_size = 2
-grad_acc_steps = 32
-n_epochs = 6
-base_LM_model = "microsoft/deberta-v3-large"
-max_seq_len = 512
-learning_rate = 7e-6
-lr_schedule = LinearWarmup
-warmup_proportion = 0.2
-doc_stride=128
-max_query_length=64
-``` 
-
-## 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/deberta-v3-large-squad2")
-# or 
-reader = TransformersReader(model_name_or_path="deepset/deberta-v3-large-squad2",tokenizer="deepset/deberta-v3-large-squad2")
-```
-
-### In Transformers
-```python
-from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
-
-model_name = "deepset/deberta-v3-large-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)
-```
-
-## Performance
-Evaluated on the SQuAD 2.0 dev set with the [official eval script](https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/).
-
-```
-"exact": 87.6105449338836,
-"f1": 90.75307008866517,
-
-"total": 11873,
-"HasAns_exact": 84.37921727395411,
-"HasAns_f1": 90.6732795483674,
-"HasAns_total": 5928,
-"NoAns_exact": 90.83263246425568,
-"NoAns_f1": 90.83263246425568,
-"NoAns_total": 5945
-```
-
-## 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://huggingface.co/spaces/deepset/README/resolve/main/haystack-logo-colored.svg" 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://huggingface.co/spaces/deepset/README/resolve/main/deepset-logo-colored.svg" 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://haystack.deepset.ai">Documentation</a></strong>. 
-
-We also have a <strong><a class="h-7" href="https://haystack.deepset.ai/community/join">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)