---
base_model: bert-base-chinese
library_name: transformers
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: weibo-model-4tags
  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. -->

# weibo-model-4tags

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: 1.0245
- Accuracy: 0.7079
- Precision: 0.7101
- Recall: 0.7079
- F1: 0.7081

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.1091        | 0.6849 | 50   | 1.0191          | 0.5361   | 0.6449    | 0.5361 | 0.4924 |
| 0.7439        | 1.3699 | 100  | 0.8837          | 0.6306   | 0.6446    | 0.6306 | 0.6280 |
| 0.7962        | 2.0548 | 150  | 0.8365          | 0.6615   | 0.6886    | 0.6615 | 0.6567 |
| 0.5132        | 2.7397 | 200  | 0.8698          | 0.6890   | 0.6977    | 0.6890 | 0.6841 |
| 0.2886        | 3.4247 | 250  | 0.9056          | 0.7096   | 0.7103    | 0.7096 | 0.7092 |
| 0.1804        | 4.1096 | 300  | 0.9927          | 0.7045   | 0.7071    | 0.7045 | 0.7027 |
| 0.146         | 4.7945 | 350  | 1.0245          | 0.7079   | 0.7101    | 0.7079 | 0.7081 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1