---
base_model: bert-base-chinese
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-finetuned-weibo-luobokuaipao
  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-finetuned-weibo-luobokuaipao

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: 3.3065
- Accuracy: 0.5833

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 270  | 0.9893          | 0.5852   |
| 1.0044        | 2.0   | 540  | 1.0391          | 0.5907   |
| 1.0044        | 3.0   | 810  | 1.2162          | 0.6130   |
| 0.5461        | 4.0   | 1080 | 1.3702          | 0.5667   |
| 0.5461        | 5.0   | 1350 | 1.8272          | 0.5704   |
| 0.349         | 6.0   | 1620 | 2.1860          | 0.5741   |
| 0.349         | 7.0   | 1890 | 2.1618          | 0.5685   |
| 0.2502        | 8.0   | 2160 | 2.5620          | 0.5593   |
| 0.2502        | 9.0   | 2430 | 2.6044          | 0.5667   |
| 0.1651        | 10.0  | 2700 | 3.0138          | 0.5778   |
| 0.1651        | 11.0  | 2970 | 3.1734          | 0.5481   |
| 0.1153        | 12.0  | 3240 | 3.0025          | 0.5759   |
| 0.0893        | 13.0  | 3510 | 3.1646          | 0.5889   |
| 0.0893        | 14.0  | 3780 | 3.0978          | 0.5833   |
| 0.0659        | 15.0  | 4050 | 3.1681          | 0.5741   |
| 0.0659        | 16.0  | 4320 | 3.1982          | 0.5778   |
| 0.0433        | 17.0  | 4590 | 3.2583          | 0.5778   |
| 0.0433        | 18.0  | 4860 | 3.2408          | 0.5778   |
| 0.0396        | 19.0  | 5130 | 3.2881          | 0.5852   |
| 0.0396        | 20.0  | 5400 | 3.3065          | 0.5833   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1