Add Japanese Sentence-BERT model trained with MultipleNegativesRankingLoss function
Browse files- 1_Pooling/config.json +7 -0
- config.json +26 -0
- config_sentence_transformers.json +7 -0
- modules.json +14 -0
- pytorch_model.bin +3 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false
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}
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config.json
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{
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"_name_or_path": "/content/model/",
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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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"classifier_dropout": null,
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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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"tokenizer_class": "BertJapaneseTokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.13.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 32768
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}
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config_sentence_transformers.json
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{
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"__version__": {
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"sentence_transformers": "2.1.0",
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"transformers": "4.13.0",
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"pytorch": "1.10.0+cu111"
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}
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}
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modules.json
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[
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{
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"idx": 0,
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"name": "0",
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"path": "",
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"type": "sentence_transformers.models.Transformer"
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},
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{
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"idx": 1,
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"name": "1",
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"path": "1_Pooling",
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"type": "sentence_transformers.models.Pooling"
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}
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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 sha256:03a998387ff05eb12021a7d16156f19ac2d05c13f67e9bcbf6b838303641fac6
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size 444910001
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sentence_bert_config.json
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{
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"max_seq_length": 80,
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"do_lower_case": false
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}
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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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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "do_lower_case": false, "do_word_tokenize": true, "do_subword_tokenize": true, "word_tokenizer_type": "mecab", "subword_tokenizer_type": "wordpiece", "never_split": null, "mecab_kwargs": {"mecab_dic": "unidic_lite"}, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "/content/allnli_model/", "tokenizer_class": "BertJapaneseTokenizer"}
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vocab.txt
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