---
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: 3.2677
- Accuracy: 0.6348

## 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   | 198  | 2.5581          | 0.5919   |
| No log        | 2.0   | 396  | 2.2918          | 0.6348   |
| 0.2014        | 3.0   | 594  | 1.9679          | 0.6348   |
| 0.2014        | 4.0   | 792  | 2.9800          | 0.6196   |
| 0.2014        | 5.0   | 990  | 2.6793          | 0.6398   |
| 0.1375        | 6.0   | 1188 | 2.8340          | 0.6247   |
| 0.1375        | 7.0   | 1386 | 2.5889          | 0.6247   |
| 0.1278        | 8.0   | 1584 | 2.3041          | 0.6725   |
| 0.1278        | 9.0   | 1782 | 2.5275          | 0.6524   |
| 0.1278        | 10.0  | 1980 | 3.1778          | 0.6171   |
| 0.0614        | 11.0  | 2178 | 2.8898          | 0.6196   |
| 0.0614        | 12.0  | 2376 | 2.7480          | 0.6322   |
| 0.028         | 13.0  | 2574 | 3.0678          | 0.6322   |
| 0.028         | 14.0  | 2772 | 3.0487          | 0.6448   |
| 0.028         | 15.0  | 2970 | 3.2878          | 0.6373   |
| 0.0177        | 16.0  | 3168 | 3.1296          | 0.6373   |
| 0.0177        | 17.0  | 3366 | 3.2056          | 0.6297   |
| 0.0193        | 18.0  | 3564 | 3.2349          | 0.6247   |
| 0.0193        | 19.0  | 3762 | 3.2624          | 0.6247   |
| 0.0193        | 20.0  | 3960 | 3.2677          | 0.6348   |


### Framework versions

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