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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
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