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.gitignore

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+checkpoint-*/

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model_index:
+- name: chinese-address-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    metric:
+      name: Accuracy
+      type: accuracy
+      value: 0.9852459016393442
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# chinese-address-ner
+
+This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext) on an unkown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0999
+- Precision: 0.9739
+- Recall: 0.9849
+- F1: 0.9794
+- Accuracy: 0.9852
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 50
+- eval_batch_size: 50
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0656        | 0.14  | 1    | 0.1061          | 0.9665    | 0.9811 | 0.9738 | 0.9844   |
+| 0.1305        | 0.29  | 2    | 0.1096          | 0.9630    | 0.9811 | 0.9720 | 0.9836   |
+| 0.1009        | 0.43  | 3    | 0.0999          | 0.9739    | 0.9849 | 0.9794 | 0.9852   |
+| 0.0844        | 0.57  | 4    | 0.0911          | 0.9739    | 0.9849 | 0.9794 | 0.9852   |
+| 0.0773        | 0.71  | 5    | 0.0858          | 0.9703    | 0.9849 | 0.9775 | 0.9852   |
+| 0.0997        | 0.86  | 6    | 0.0815          | 0.9739    | 0.9849 | 0.9794 | 0.9861   |
+| 0.0904        | 1.0   | 7    | 0.0795          | 0.9739    | 0.9849 | 0.9794 | 0.9861   |
+
+
+### Framework versions
+
+- Transformers 4.8.2
+- Pytorch 1.7.0
+- Datasets 1.9.0
+- Tokenizers 0.10.3

config.json

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 {
-  "_name_or_path": "./temp",
+  "_name_or_path": "hfl/chinese-roberta-wwm-ext",
   "architectures": [
-    "BertModel"
+    "BertForTokenClassification"
   ],
   "attention_probs_dropout_prob": 0.1,
   "bos_token_id": 0,

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special_tokens_map.json

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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, "special_tokens_map_file": "/Users/jiaqianjing/.cache/huggingface/transformers/d521373fc7ac35f63d56cf303de74a202403dcf1aaa792cd01f653694be59563.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "hfl/chinese-roberta-wwm-ext", "tokenizer_class": "BertTokenizer"}

training_args.bin

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