Initial Dump
Browse files- README.md +252 -0
- config.json +29 -0
- merges.txt +0 -0
- special_tokens_map.json +15 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- vocab.json +0 -0
README.md
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---
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license: cc-by-4.0
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---
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---
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language: en
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license: cc-by-4.0
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datasets:
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- squad_v2
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model-index:
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- name: deepset/tinyroberta-squad2
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results:
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: squad_v2
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type: squad_v2
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config: squad_v2
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split: validation
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metrics:
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- type: exact_match
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value: 78.8627
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name: Exact Match
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verified: true
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+
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDNlZDU4ODAxMzY5NGFiMTMyZmQ1M2ZhZjMyODA1NmFlOGMxNzYxNTA4OGE5YTBkZWViZjBkNGQ2ZmMxZjVlMCIsInZlcnNpb24iOjF9.Wgu599r6TvgMLTrHlLMVAbUtKD_3b70iJ5QSeDQ-bRfUsVk6Sz9OsJCp47riHJVlmSYzcDj_z_3jTcUjCFFXBg
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+
- type: f1
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+
value: 82.0355
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+
name: F1
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+
verified: true
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+
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTFkMzEzMWNiZDRhMGZlODhkYzcwZTZiMDFjZDg2YjllZmUzYWM5NTgwNGQ2NGYyMDk2ZGQwN2JmMTE5NTc3YiIsInZlcnNpb24iOjF9.ChgaYpuRHd5WeDFjtiAHUyczxtoOD_M5WR8834jtbf7wXhdGOnZKdZ1KclmhoI5NuAGc1NptX-G0zQ5FTHEcBA
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: squad
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type: squad
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config: plain_text
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split: validation
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metrics:
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- type: exact_match
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value: 83.860
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name: Exact Match
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+
- type: f1
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value: 90.752
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+
name: F1
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+
- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: adversarial_qa
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type: adversarial_qa
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config: adversarialQA
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split: validation
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metrics:
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- type: exact_match
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value: 25.967
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name: Exact Match
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+
- type: f1
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value: 37.006
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name: F1
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: squad_adversarial
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type: squad_adversarial
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config: AddOneSent
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split: validation
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metrics:
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- type: exact_match
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value: 76.329
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name: Exact Match
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- type: f1
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value: 83.292
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name: F1
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: squadshifts amazon
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type: squadshifts
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config: amazon
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split: test
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metrics:
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- type: exact_match
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value: 63.915
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name: Exact Match
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- type: f1
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value: 78.395
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name: F1
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: squadshifts new_wiki
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type: squadshifts
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config: new_wiki
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split: test
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metrics:
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- type: exact_match
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value: 80.297
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name: Exact Match
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- type: f1
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value: 89.808
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name: F1
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+
- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: squadshifts nyt
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type: squadshifts
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config: nyt
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split: test
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metrics:
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- type: exact_match
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value: 80.149
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name: Exact Match
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- type: f1
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value: 88.321
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name: F1
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: squadshifts reddit
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type: squadshifts
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config: reddit
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split: test
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metrics:
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- type: exact_match
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value: 66.959
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name: Exact Match
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- type: f1
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value: 79.300
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name: F1
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---
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**This repo contains the model exported to ONNX weights.**
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**Everything is provided as-is.**
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---
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# tinyroberta-squad2
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This is the *distilled* version of the [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) model. This model has a comparable prediction quality and runs at twice the speed of the base model.
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## Overview
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**Language model:** tinyroberta-squad2
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**Language:** English
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**Downstream-task:** Extractive QA
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**Training data:** SQuAD 2.0
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**Eval data:** SQuAD 2.0
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**Code:** See [an example QA pipeline on Haystack](https://haystack.deepset.ai/tutorials/first-qa-system)
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**Infrastructure**: 4x Tesla v100
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## Hyperparameters
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```
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batch_size = 96
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n_epochs = 4
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base_LM_model = "deepset/tinyroberta-squad2-step1"
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max_seq_len = 384
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learning_rate = 3e-5
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lr_schedule = LinearWarmup
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warmup_proportion = 0.2
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doc_stride = 128
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max_query_length = 64
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distillation_loss_weight = 0.75
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temperature = 1.5
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teacher = "deepset/robert-large-squad2"
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```
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## Distillation
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This model was distilled using the TinyBERT approach described in [this paper](https://arxiv.org/pdf/1909.10351.pdf) and implemented in [haystack](https://github.com/deepset-ai/haystack).
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Firstly, we have performed intermediate layer distillation with roberta-base as the teacher which resulted in [deepset/tinyroberta-6l-768d](https://huggingface.co/deepset/tinyroberta-6l-768d).
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Secondly, we have performed task-specific distillation with [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) as the teacher for further intermediate layer distillation on an augmented version of SQuADv2 and then with [deepset/roberta-large-squad2](https://huggingface.co/deepset/roberta-large-squad2) as the teacher for prediction layer distillation.
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## Usage
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### In Haystack
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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/):
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```python
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reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2")
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# or
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reader = TransformersReader(model_name_or_path="deepset/tinyroberta-squad2")
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```
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### In Transformers
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```python
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from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
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model_name = "deepset/tinyroberta-squad2"
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# a) Get predictions
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nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
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QA_input = {
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'question': 'Why is model conversion important?',
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'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
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}
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res = nlp(QA_input)
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# b) Load model & tokenizer
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model = AutoModelForQuestionAnswering.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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```
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## Performance
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Evaluated on the SQuAD 2.0 dev set with the [official eval script](https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/).
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```
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"exact": 78.69114798281817,
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"f1": 81.9198998536977,
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"total": 11873,
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"HasAns_exact": 76.19770580296895,
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"HasAns_f1": 82.66446878592329,
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"HasAns_total": 5928,
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"NoAns_exact": 81.17746005046257,
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"NoAns_f1": 81.17746005046257,
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"NoAns_total": 5945
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```
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## Authors
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**Branden Chan:** branden.chan@deepset.ai
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**Timo Möller:** timo.moeller@deepset.ai
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**Malte Pietsch:** malte.pietsch@deepset.ai
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**Tanay Soni:** tanay.soni@deepset.ai
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**Michel Bartels:** michel.bartels@deepset.ai
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## About us
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<div class="grid lg:grid-cols-2 gap-x-4 gap-y-3">
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<div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
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<img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/deepset-logo-colored.png" class="w-40"/>
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</div>
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<div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
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<img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/haystack-logo-colored.png" class="w-40"/>
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</div>
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</div>
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[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.
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Some of our other work:
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- [roberta-base-squad2]([https://huggingface.co/deepset/roberta-base-squad2)
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- [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
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- [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
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## Get in touch and join the Haystack community
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<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>.
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We also have a <strong><a class="h-7" href="https://haystack.deepset.ai/community/join">Discord community open to everyone!</a></strong></p>
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[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Discord](https://haystack.deepset.ai/community) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)
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By the way: [we're hiring!](http://www.deepset.ai/jobs)
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config.json
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{
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"_name_or_path": "deepset/tinyroberta-squad2",
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"architectures": [
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"RobertaForQuestionAnswering"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"language": "english",
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"name": "Roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"transformers_version": "4.35.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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merges.txt
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special_tokens_map.json
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|
1 |
+
{
|
2 |
+
"bos_token": "<s>",
|
3 |
+
"cls_token": "<s>",
|
4 |
+
"eos_token": "</s>",
|
5 |
+
"mask_token": {
|
6 |
+
"content": "<mask>",
|
7 |
+
"lstrip": true,
|
8 |
+
"normalized": false,
|
9 |
+
"rstrip": false,
|
10 |
+
"single_word": false
|
11 |
+
},
|
12 |
+
"pad_token": "<pad>",
|
13 |
+
"sep_token": "</s>",
|
14 |
+
"unk_token": "<unk>"
|
15 |
+
}
|
tokenizer.json
ADDED
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tokenizer_config.json
ADDED
@@ -0,0 +1,57 @@
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|
1 |
+
{
|
2 |
+
"add_prefix_space": false,
|
3 |
+
"added_tokens_decoder": {
|
4 |
+
"0": {
|
5 |
+
"content": "<s>",
|
6 |
+
"lstrip": false,
|
7 |
+
"normalized": false,
|
8 |
+
"rstrip": false,
|
9 |
+
"single_word": false,
|
10 |
+
"special": true
|
11 |
+
},
|
12 |
+
"1": {
|
13 |
+
"content": "<pad>",
|
14 |
+
"lstrip": false,
|
15 |
+
"normalized": false,
|
16 |
+
"rstrip": false,
|
17 |
+
"single_word": false,
|
18 |
+
"special": true
|
19 |
+
},
|
20 |
+
"2": {
|
21 |
+
"content": "</s>",
|
22 |
+
"lstrip": false,
|
23 |
+
"normalized": false,
|
24 |
+
"rstrip": false,
|
25 |
+
"single_word": false,
|
26 |
+
"special": true
|
27 |
+
},
|
28 |
+
"3": {
|
29 |
+
"content": "<unk>",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": false,
|
32 |
+
"rstrip": false,
|
33 |
+
"single_word": false,
|
34 |
+
"special": true
|
35 |
+
},
|
36 |
+
"50264": {
|
37 |
+
"content": "<mask>",
|
38 |
+
"lstrip": true,
|
39 |
+
"normalized": false,
|
40 |
+
"rstrip": false,
|
41 |
+
"single_word": false,
|
42 |
+
"special": true
|
43 |
+
}
|
44 |
+
},
|
45 |
+
"bos_token": "<s>",
|
46 |
+
"clean_up_tokenization_spaces": true,
|
47 |
+
"cls_token": "<s>",
|
48 |
+
"eos_token": "</s>",
|
49 |
+
"errors": "replace",
|
50 |
+
"mask_token": "<mask>",
|
51 |
+
"model_max_length": 512,
|
52 |
+
"pad_token": "<pad>",
|
53 |
+
"sep_token": "</s>",
|
54 |
+
"tokenizer_class": "RobertaTokenizer",
|
55 |
+
"trim_offsets": true,
|
56 |
+
"unk_token": "<unk>"
|
57 |
+
}
|
vocab.json
ADDED
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|
|