---
license: mit
base_model: tangminhanh/cate-ts
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: subcate-ts
  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. -->

# subcate-ts

This model is a fine-tuned version of [tangminhanh/cate-ts](https://huggingface.co/tangminhanh/cate-ts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0130
- Accuracy: 0.3377
- F1: 0.4963
- Precision: 0.9460
- Recall: 0.3364

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8242        | 0.9987 | 188  | 0.2821          | 0.0      | 0.0081 | 0.0046    | 0.0321 |
| 0.1451        | 1.9973 | 376  | 0.0313          | 0.0      | 0.0    | 0.0       | 0.0    |
| 0.0298        | 2.9960 | 564  | 0.0231          | 0.0      | 0.0    | 0.0       | 0.0    |
| 0.024         | 4.0    | 753  | 0.0206          | 0.0      | 0.0    | 0.0       | 0.0    |
| 0.0212        | 4.9987 | 941  | 0.0181          | 0.1261   | 0.2233 | 0.9922    | 0.1258 |
| 0.0187        | 5.9973 | 1129 | 0.0162          | 0.2292   | 0.3696 | 0.9664    | 0.2285 |
| 0.0169        | 6.9960 | 1317 | 0.0147          | 0.3081   | 0.4657 | 0.9646    | 0.3070 |
| 0.0157        | 8.0    | 1506 | 0.0137          | 0.3184   | 0.4763 | 0.9551    | 0.3172 |
| 0.0151        | 8.9987 | 1694 | 0.0132          | 0.3310   | 0.4894 | 0.9486    | 0.3298 |
| 0.0145        | 9.9867 | 1880 | 0.0130          | 0.3377   | 0.4963 | 0.9460    | 0.3364 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1