---
library_name: transformers
base_model: bert-base-chinese
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-chinese-finetuned-paragraph_extraction-retrain3
  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-paragraph_extraction-retrain3

This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2350
- Accuracy: 0.9538

## 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: 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: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.1994        | 0.1842 | 2000  | 0.2304          | 0.9395   |
| 0.2139        | 0.3684 | 4000  | 0.3441          | 0.9242   |
| 0.2433        | 0.5526 | 6000  | 0.2450          | 0.9528   |
| 0.1658        | 0.7369 | 8000  | 0.1913          | 0.9548   |
| 0.1741        | 0.9211 | 10000 | 0.2350          | 0.9538   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1