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基于10w基金行业短句训练的中文情感分析 0: 'negative', 1: 'positive', 2: 'neutral',
验证集准确度: 0.9382193411826961
验证集分类报告:
precision recall f1-score support

negative 0.93 0.95 0.94 3785
positive 0.95 0.96 0.95 6919
neutral 0.93 0.89 0.91 4414

accuracy 0.94 15118
macro avg 0.94 0.93 0.93 15118
weighted avg 0.94 0.94 0.94 15118

config.json ADDED
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+ {
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+ "_name_or_path": "/mnt/chinese",
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+ "architectures": [
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+ "BertForSequenceClassification"
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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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+ "directionality": "bidi",
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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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+ "id2label": {
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+ "0": "LABEL_0",
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+ "2": "LABEL_2"
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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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+ "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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+ "torch_dtype": "float32",
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+ "transformers_version": "4.18.0",
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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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special_tokens_map.json ADDED
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+ {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
tokenizer_config.json ADDED
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vocab.txt ADDED
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