---
license: gpl-3.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-chinese-finetuned-ner_0220_J_ORIDATA_FULL_NOMOD
  results: []
---

<!-- 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. -->

# bert-base-chinese-finetuned-ner_0220_J_ORIDATA_FULL_NOMOD

This model is a fine-tuned version of [ckiplab/bert-base-chinese-ner](https://huggingface.co/ckiplab/bert-base-chinese-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3786
- Precision: 0.9357
- Recall: 0.9657
- F1: 0.9504
- Accuracy: 0.9577

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0925        | 1.0   | 5358  | 0.2337          | 0.9246    | 0.9655 | 0.9446 | 0.9554   |
| 0.0787        | 2.0   | 10716 | 0.2506          | 0.9208    | 0.9588 | 0.9394 | 0.9525   |
| 0.0606        | 3.0   | 16074 | 0.2914          | 0.9309    | 0.9621 | 0.9462 | 0.9537   |
| 0.0543        | 4.0   | 21432 | 0.2792          | 0.9248    | 0.9633 | 0.9437 | 0.9553   |
| 0.056         | 5.0   | 26790 | 0.3064          | 0.9332    | 0.9645 | 0.9486 | 0.9563   |
| 0.0384        | 6.0   | 32148 | 0.3317          | 0.9347    | 0.9632 | 0.9487 | 0.9564   |
| 0.0265        | 7.0   | 37506 | 0.3340          | 0.9342    | 0.9667 | 0.9502 | 0.9568   |
| 0.03          | 8.0   | 42864 | 0.3460          | 0.9363    | 0.9641 | 0.9500 | 0.9558   |
| 0.0192        | 9.0   | 48222 | 0.3649          | 0.9357    | 0.9651 | 0.9501 | 0.9576   |
| 0.0117        | 10.0  | 53580 | 0.3786          | 0.9357    | 0.9657 | 0.9504 | 0.9577   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.13.0+cu117
- Datasets 2.8.0
- Tokenizers 0.12.1