---
base_model: jinmang2/kpfbert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: model_y3_research_1
  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. -->

# model_y3_research_1

This model is a fine-tuned version of [jinmang2/kpfbert](https://huggingface.co/jinmang2/kpfbert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7692
- Accuracy: 0.6082
- F1: 0.5677
- Precision: 0.5728
- Recall: 0.5706

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9518        | 1.0   | 97   | 1.0302          | 0.4167   | 0.2266 | 0.2376    | 0.3280 |
| 0.9191        | 2.0   | 194  | 0.9158          | 0.5833   | 0.5823 | 0.6203    | 0.6297 |
| 0.8298        | 3.0   | 291  | 0.8410          | 0.6042   | 0.5903 | 0.5987    | 0.5848 |
| 0.7093        | 4.0   | 388  | 1.1104          | 0.5208   | 0.5176 | 0.5135    | 0.5312 |
| 0.5994        | 5.0   | 485  | 1.3535          | 0.5521   | 0.5437 | 0.5691    | 0.5555 |
| 0.709         | 6.0   | 582  | 1.8616          | 0.5104   | 0.4892 | 0.4975    | 0.5019 |
| 0.2919        | 7.0   | 679  | 2.5441          | 0.5208   | 0.5174 | 0.5164    | 0.5340 |
| 0.1296        | 8.0   | 776  | 2.9520          | 0.5104   | 0.4975 | 0.5103    | 0.4931 |
| 0.0012        | 9.0   | 873  | 3.1406          | 0.5312   | 0.5182 | 0.5165    | 0.5209 |
| 0.0393        | 10.0  | 970  | 3.1606          | 0.5208   | 0.5109 | 0.5084    | 0.5142 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2