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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
|