---
library_name: transformers
license: apache-2.0
base_model: hfl/chinese-bert-wwm-ext
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_model
  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_model

This model is a fine-tuned version of [hfl/chinese-bert-wwm-ext](https://huggingface.co/hfl/chinese-bert-wwm-ext) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0311
- Precision: 1.0000
- Recall: 1.0000
- F1: 1.0000
- Accuracy: 1.0000

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- 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: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.031         | 1.0   | 15055 | 0.0317          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |
| 0.031         | 2.0   | 30110 | 0.0313          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |
| 0.031         | 3.0   | 45165 | 0.0312          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |
| 0.031         | 4.0   | 60220 | 0.0311          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |
| 0.031         | 5.0   | 75275 | 0.0311          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1