---
license: mit
base_model: tangminhanh/ts_tg
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ts_cate
  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. -->

# ts_cate

This model is a fine-tuned version of [tangminhanh/ts_tg](https://huggingface.co/tangminhanh/ts_tg) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0263
- Accuracy: 0.8555
- F1: 0.8736
- Precision: 0.8824
- Recall: 0.8649

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 404  | 0.0458          | 0.6802   | 0.7650 | 0.8750    | 0.6796 |
| 0.1001        | 2.0   | 808  | 0.0318          | 0.7717   | 0.8259 | 0.8817    | 0.7767 |
| 0.0321        | 3.0   | 1212 | 0.0278          | 0.8251   | 0.8564 | 0.8862    | 0.8286 |
| 0.0215        | 4.0   | 1616 | 0.0256          | 0.8322   | 0.8627 | 0.8909    | 0.8363 |
| 0.0161        | 5.0   | 2020 | 0.0256          | 0.8455   | 0.8679 | 0.8812    | 0.8551 |
| 0.0161        | 6.0   | 2424 | 0.0259          | 0.8499   | 0.8711 | 0.8831    | 0.8594 |
| 0.0124        | 7.0   | 2828 | 0.0255          | 0.8536   | 0.8713 | 0.8836    | 0.8594 |
| 0.0105        | 8.0   | 3232 | 0.0262          | 0.8533   | 0.8723 | 0.8836    | 0.8612 |
| 0.0087        | 9.0   | 3636 | 0.0261          | 0.8567   | 0.8746 | 0.8838    | 0.8656 |
| 0.0078        | 10.0  | 4040 | 0.0263          | 0.8555   | 0.8736 | 0.8824    | 0.8649 |


### Framework versions

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