Upload 6 files
Browse files- all_results.json +1 -0
- config.json +53 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer_config.json +16 -0
- vocab.txt +0 -0
all_results.json
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{"eval_f1": 0.9088937093275489}
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config.json
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{
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"_name_or_path": "thunlp/Lawformer",
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"architectures": [
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"LongformerForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"attention_window": [
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512,
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512,
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512,
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512,
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512,
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512,
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512,
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512,
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512,
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512,
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512,
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512
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],
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"bos_token_id": 0,
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"classifier_dropout": null,
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"directionality": "bidi",
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"eos_token_id": 2,
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"finetuning_task": "RM",
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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": 4098,
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"model_type": "longformer",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"onnx_export": false,
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"output_past": true,
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"pad_token_id": 1,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"sep_token_id": 2,
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"torch_dtype": "float32",
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"transformers_version": "4.22.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 21128
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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 sha256:1d25b32daf6c2c15b0e4febd7853249d48d9006d0d38e2314462854c90488c88
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size 505231263
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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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_config.json
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{
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"name_or_path": "hfl/chinese-roberta-wwm-ext",
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": "/home/yangzhanye/.cache/huggingface/hub/models--hfl--chinese-roberta-wwm-ext/snapshots/5c58d0b8ec1d9014354d691c538661bf00bfdb44/special_tokens_map.json",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]",
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"use_fast": true
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}
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vocab.txt
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