Shobhank-iiitdwd
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Browse files- README.md +80 -0
- config.json +26 -0
- index.gitattributes +27 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
README.md
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---
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language: en
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license: mit
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tags:
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- exbert
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datasets:
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- squad_v2
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thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
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model-index:
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- name: deepset/bert-medium-squad2-distilled
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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: 69.8231
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name: Exact Match
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmE4MGRkZTVjNmViMGNjYjVhY2E1NzcyOGQ1OWE1MWMzMjY5NWU0MmU0Y2I4OWU4YTU5OWQ5YTI2NWE1NmM0ZSIsInZlcnNpb24iOjF9.tnCJvWzMctTwiQu5yig_owO2ZI1t1MZz1AN2lQy4COAGOzuMovD-74acQvMbxJQoRfNNkIetz2hqYivf1lJKDw
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- type: f1
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value: 72.9232
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name: F1
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTMwNzk0ZDRjNGUyMjQyNzc1NzczZmUwMTU2MTM5MGQ3M2NhODlmOTU4ZDI0YjhlNTVjNDA1MGEwM2M1MzIyZSIsInZlcnNpb24iOjF9.eElGmTOXH_qHTNaPwZ-dUJfVz9VMvCutDCof_6UG_625MwctT_j7iVkWcGwed4tUnunuq1BPm-0iRh1RuuB-AQ
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---
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## Overview
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**Language model:** deepset/roberta-base-squad2-distilled
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**Language:** English
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**Training data:** SQuAD 2.0 training set
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**Eval data:** SQuAD 2.0 dev set
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**Infrastructure**: 1x V100 GPU
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**Published**: Apr 21st, 2021
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## Details
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- haystack's distillation feature was used for training. deepset/bert-large-uncased-whole-word-masking-squad2 was used as the teacher model.
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## Hyperparameters
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```
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batch_size = 6
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n_epochs = 2
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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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embeds_dropout_prob = 0.1
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temperature = 5
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distillation_loss_weight = 1
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```
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## Performance
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```
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"exact": 68.6431398972458
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"f1": 72.7637083790805
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```
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## Authors
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- Timo Möller: `timo.moeller [at] deepset.ai`
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- Julian Risch: `julian.risch [at] deepset.ai`
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- Malte Pietsch: `malte.pietsch [at] deepset.ai`
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- Michel Bartels: `michel.bartels [at] deepset.ai`
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## About us
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![deepset logo](https://workablehr.s3.amazonaws.com/uploads/account/logo/476306/logo)
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We bring NLP to the industry via open source!
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Our focus: Industry specific language models & large scale QA systems.
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Some of our work:
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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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- [FARM](https://github.com/deepset-ai/FARM)
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- [Haystack](https://github.com/deepset-ai/haystack/)
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Get in touch:
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[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)
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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": "roberta-base-squad2/language_model.bin",
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"architectures": [
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"BertForQuestionAnswering"
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],
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"attention_probs_dropout_prob": 0.1,
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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": 512,
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"initializer_range": 0.02,
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"intermediate_size": 2048,
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"language": "english",
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"name": "Bert",
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"num_attention_heads": 8,
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"num_hidden_layers": 8,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.7.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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index.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a9c401109aa56e44e00783606661a8e0fbc14ec96c71f465513d7854ef91564a
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size 164503793
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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]"}
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tokenizer.json
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tokenizer_config.json
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "roberta-base-squad2", "do_basic_tokenize": true, "never_split": null, "model_max_length": 512}
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vocab.txt
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