---
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: 3.2017
- Accuracy: 0.5815

## 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: 1e-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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 243  | 1.0137          | 0.5852   |
| No log        | 2.0   | 486  | 0.9878          | 0.5815   |
| 1.0413        | 3.0   | 729  | 1.0463          | 0.6056   |
| 1.0413        | 4.0   | 972  | 1.1697          | 0.6130   |
| 0.5875        | 5.0   | 1215 | 1.3835          | 0.5852   |
| 0.5875        | 6.0   | 1458 | 1.5941          | 0.5722   |
| 0.3069        | 7.0   | 1701 | 1.9360          | 0.5796   |
| 0.3069        | 8.0   | 1944 | 2.0863          | 0.6093   |
| 0.1782        | 9.0   | 2187 | 2.2601          | 0.5833   |
| 0.1782        | 10.0  | 2430 | 2.4810          | 0.5926   |
| 0.12          | 11.0  | 2673 | 2.5233          | 0.6      |
| 0.12          | 12.0  | 2916 | 2.5486          | 0.5833   |
| 0.089         | 13.0  | 3159 | 2.6555          | 0.5704   |
| 0.089         | 14.0  | 3402 | 2.6093          | 0.6019   |
| 0.0718        | 15.0  | 3645 | 2.6888          | 0.5907   |
| 0.0718        | 16.0  | 3888 | 2.9839          | 0.5722   |
| 0.061         | 17.0  | 4131 | 2.8104          | 0.5778   |
| 0.061         | 18.0  | 4374 | 2.9843          | 0.5685   |
| 0.062         | 19.0  | 4617 | 3.1577          | 0.5648   |
| 0.062         | 20.0  | 4860 | 3.1641          | 0.5722   |
| 0.0553        | 21.0  | 5103 | 3.1004          | 0.5611   |
| 0.0553        | 22.0  | 5346 | 3.0974          | 0.5778   |
| 0.0417        | 23.0  | 5589 | 3.0206          | 0.5759   |
| 0.0417        | 24.0  | 5832 | 3.0191          | 0.5667   |
| 0.0374        | 25.0  | 6075 | 3.0920          | 0.5722   |
| 0.0374        | 26.0  | 6318 | 2.9696          | 0.5852   |
| 0.0335        | 27.0  | 6561 | 3.0100          | 0.5889   |
| 0.0335        | 28.0  | 6804 | 3.1014          | 0.5667   |
| 0.0313        | 29.0  | 7047 | 3.2620          | 0.5574   |
| 0.0313        | 30.0  | 7290 | 3.0502          | 0.5889   |
| 0.032         | 31.0  | 7533 | 3.0984          | 0.5833   |
| 0.032         | 32.0  | 7776 | 3.1546          | 0.5704   |
| 0.0329        | 33.0  | 8019 | 3.0977          | 0.5741   |
| 0.0329        | 34.0  | 8262 | 3.0975          | 0.5796   |
| 0.0276        | 35.0  | 8505 | 3.1124          | 0.5870   |
| 0.0276        | 36.0  | 8748 | 3.1204          | 0.5926   |
| 0.0276        | 37.0  | 8991 | 3.1556          | 0.5833   |
| 0.026         | 38.0  | 9234 | 3.1909          | 0.5815   |
| 0.026         | 39.0  | 9477 | 3.1959          | 0.5815   |
| 0.0245        | 40.0  | 9720 | 3.2017          | 0.5815   |


### Framework versions

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