---
license: mit
base_model: tangminhanh/ts_cate
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ts_subcate
  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_subcate

This model is a fine-tuned version of [tangminhanh/ts_cate](https://huggingface.co/tangminhanh/ts_cate) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0084
- Accuracy: 0.7013
- F1: 0.7812
- Precision: 0.8815
- Recall: 0.7014

## 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   | 403  | 0.0261          | 0.0      | 0.0    | 0.0       | 0.0    |
| 0.0805        | 2.0   | 806  | 0.0174          | 0.3328   | 0.4904 | 0.9438    | 0.3313 |
| 0.0203        | 3.0   | 1209 | 0.0131          | 0.4702   | 0.6217 | 0.9229    | 0.4687 |
| 0.0138        | 4.0   | 1612 | 0.0111          | 0.5592   | 0.6939 | 0.9170    | 0.5581 |
| 0.0104        | 5.0   | 2015 | 0.0100          | 0.6297   | 0.7417 | 0.8998    | 0.6308 |
| 0.0104        | 6.0   | 2418 | 0.0091          | 0.6659   | 0.7628 | 0.8909    | 0.6669 |
| 0.0084        | 7.0   | 2821 | 0.0088          | 0.6815   | 0.7712 | 0.8867    | 0.6823 |
| 0.0072        | 8.0   | 3224 | 0.0086          | 0.6889   | 0.7764 | 0.8874    | 0.6900 |
| 0.0063        | 9.0   | 3627 | 0.0084          | 0.6982   | 0.7803 | 0.8832    | 0.6989 |
| 0.006         | 10.0  | 4030 | 0.0084          | 0.7013   | 0.7812 | 0.8815    | 0.7014 |


### Framework versions

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