hardyqr
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Commit
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5eccb21
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upload the model
Browse files- README.md +20 -0
- config.json +24 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -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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tags:
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- sentence-embeddings
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- sentence-similarity
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### mirror-bert-base-uncased-sentence-drophead
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An unsupervised sentence encoder proposed by [Liu et al. (2021)](https://arxiv.org/pdf/2104.08027.pdf), using [drophead](https://aclanthology.org/2020.findings-emnlp.178.pdf) instead of dropout as feature space augmentation. Trained with unlabelled raw sentences, using [bert-base-uncased](https://huggingface.co/bert-base-uncased) as the base model. Please use mean-pooling over *all tokens* as the representation of the input.
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### Citation
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```bibtex
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@inproceedings{
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liu2021fast,
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title={Fast, Effective and Self-Supervised: Transforming Masked LanguageModels into Universal Lexical and Sentence Encoders},
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author={Liu, Fangyu and Vuli{\'c}, Ivan and Korhonen, Anna and Collier, Nigel},
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booktitle={EMNLP 2021},
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year={2021}
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}
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```
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config.json
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{
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"_name_or_path": "bert-base-uncased",
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"architectures": [
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"BertModel"
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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": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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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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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.2.1",
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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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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:0b42fb54bf6b691b82d5ec0ada5f506d6d9c255fe391d2a34d1a9d523410f3af
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size 438015479
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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_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, "model_max_length": 512, "name_or_path": "bert-base-uncased"}
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vocab.txt
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