---
license: gpl-3.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-chinese-finetuned-ner_0301_J_DATA
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-chinese-finetuned-ner_0301_J_DATA

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: 0.0318
- Precision: 0.9551
- Recall: 0.9787
- F1: 0.9668
- Accuracy: 0.9923

## 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: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.352         | 1.0   | 705   | 0.0754          | 0.8558    | 0.9182 | 0.8859 | 0.9774   |
| 0.0636        | 2.0   | 1410  | 0.0928          | 0.9082    | 0.9428 | 0.9252 | 0.9794   |
| 0.025         | 3.0   | 2115  | 0.0576          | 0.9262    | 0.9574 | 0.9416 | 0.9828   |
| 0.0253        | 4.0   | 2820  | 0.0801          | 0.9419    | 0.9630 | 0.9523 | 0.9824   |
| 0.0169        | 5.0   | 3525  | 0.0400          | 0.9287    | 0.9641 | 0.9461 | 0.9886   |
| 0.0108        | 6.0   | 4230  | 0.0370          | 0.9372    | 0.9709 | 0.9537 | 0.9903   |
| 0.0143        | 7.0   | 4935  | 0.0430          | 0.9308    | 0.9652 | 0.9477 | 0.9855   |
| 0.0083        | 8.0   | 5640  | 0.0648          | 0.9382    | 0.9709 | 0.9543 | 0.9877   |
| 0.0057        | 9.0   | 6345  | 0.0269          | 0.9222    | 0.9697 | 0.9454 | 0.9903   |
| 0.0036        | 10.0  | 7050  | 0.0338          | 0.9464    | 0.9697 | 0.9579 | 0.9927   |
| 0.003         | 11.0  | 7755  | 0.0486          | 0.9581    | 0.9742 | 0.9661 | 0.9894   |
| 0.0017        | 12.0  | 8460  | 0.0230          | 0.9593    | 0.9765 | 0.9678 | 0.9909   |
| 0.001         | 13.0  | 9165  | 0.0260          | 0.9508    | 0.9753 | 0.9629 | 0.9949   |
| 0.0014        | 14.0  | 9870  | 0.0357          | 0.9582    | 0.9765 | 0.9672 | 0.9914   |
| 0.0008        | 15.0  | 10575 | 0.0318          | 0.9551    | 0.9787 | 0.9668 | 0.9923   |


### Framework versions

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