KoichiYasuoka
commited on
Commit
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Parent(s):
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model improved
Browse files- README.md +1 -1
- config.json +7 -4
- pytorch_model.bin +2 -2
- special_tokens_map.json +9 -1
- tokenizer.json +0 -0
- tokenizer_config.json +14 -1
README.md
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## Model Description
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This is a DeBERTa(V2) model pre-trained on 青空文庫 texts. You can fine-tune `deberta-small-japanese-aozora` for downstream tasks, such as [POS-tagging](https://huggingface.co/KoichiYasuoka/deberta-small-japanese-luw-upos), dependency-parsing, and so on.
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## How to Use
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## Model Description
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This is a DeBERTa(V2) model pre-trained on 青空文庫 texts. NVIDIA A100-SXM4-40GB took 6 hours 42 minutes for training. You can fine-tune `deberta-small-japanese-aozora` for downstream tasks, such as [POS-tagging](https://huggingface.co/KoichiYasuoka/deberta-small-japanese-luw-upos), dependency-parsing, and so on.
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## How to Use
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config.json
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"pooler_dropout": 0,
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"pooler_hidden_act": "gelu",
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"pooler_hidden_size": 256,
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"pos_att_type":
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"tokenizer_class": "DebertaV2TokenizerFast",
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"torch_dtype": "float32",
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"transformers_version": "4.
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"type_vocab_size": 0,
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"vocab_size": 32000
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}
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"pooler_dropout": 0,
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"pooler_hidden_act": "gelu",
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"pooler_hidden_size": 256,
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"pos_att_type": [
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"p2c",
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"c2p"
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],
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"position_biased_input": false,
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"relative_attention": true,
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"tokenizer_class": "DebertaV2TokenizerFast",
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"torch_dtype": "float32",
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"transformers_version": "4.22.1",
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"type_vocab_size": 0,
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"vocab_size": 32000
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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:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:737de6396255e10ac75849033efbea2a4eaf0d82ba00a5140099234b804134fb
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size 71432141
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special_tokens_map.json
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{
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{
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"eos_token": "[SEP]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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See raw diff
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tokenizer_config.json
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{
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{
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"eos_token": "[SEP]",
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"keep_accents": true,
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"mask_token": "[MASK]",
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"model_max_length": 128,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"split_by_punct": true,
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"tokenizer_class": "DebertaV2TokenizerFast",
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"unk_token": "[UNK]"
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}
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