---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-chinese
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_based_bert-base-chinese_withBadcase_replaceSpace
  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. -->

# ner_based_bert-base-chinese_withBadcase_replaceSpace

This model is a fine-tuned version of [google-bert/bert-base-chinese](https://huggingface.co/google-bert/bert-base-chinese) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0138
- Precision: 0.9505
- Recall: 0.9655
- F1: 0.9579
- Accuracy: 0.9969

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- training_steps: 6520
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1507        | 1.0   | 652  | 0.0249          | 0.8949    | 0.9105 | 0.9026 | 0.9928   |
| 0.0256        | 2.0   | 1304 | 0.0189          | 0.9186    | 0.9245 | 0.9215 | 0.9945   |
| 0.0195        | 3.0   | 1956 | 0.0169          | 0.9237    | 0.9470 | 0.9352 | 0.9952   |
| 0.0131        | 4.0   | 2608 | 0.0161          | 0.9299    | 0.9499 | 0.9398 | 0.9956   |
| 0.0114        | 5.0   | 3260 | 0.0149          | 0.9311    | 0.9607 | 0.9457 | 0.9959   |
| 0.01          | 6.0   | 3912 | 0.0146          | 0.9395    | 0.9600 | 0.9497 | 0.9962   |
| 0.0072        | 7.0   | 4564 | 0.0139          | 0.9480    | 0.9562 | 0.9521 | 0.9965   |
| 0.0065        | 8.0   | 5216 | 0.0133          | 0.9431    | 0.9655 | 0.9542 | 0.9966   |
| 0.0059        | 9.0   | 5868 | 0.0134          | 0.9501    | 0.9640 | 0.9570 | 0.9968   |
| 0.0042        | 10.0  | 6520 | 0.0138          | 0.9505    | 0.9655 | 0.9579 | 0.9969   |


### Framework versions

- Transformers 4.54.0
- Pytorch 2.7.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4