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

# cs_subcate

This model is a fine-tuned version of [tangminhanh/ts_subcate](https://huggingface.co/tangminhanh/ts_subcate) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0517
- Accuracy: 0.6283
- F1: 0.6777
- Precision: 0.7292
- Recall: 0.6330

## 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   | 195  | 0.0649          | 0.2715   | 0.4110 | 0.8554    | 0.2704 |
| No log        | 2.0   | 390  | 0.0532          | 0.5113   | 0.6149 | 0.7639    | 0.5145 |
| 0.0785        | 3.0   | 585  | 0.0515          | 0.5688   | 0.6404 | 0.7225    | 0.5750 |
| 0.0785        | 4.0   | 780  | 0.0496          | 0.5979   | 0.6606 | 0.7225    | 0.6085 |
| 0.0785        | 5.0   | 975  | 0.0492          | 0.6147   | 0.6753 | 0.7367    | 0.6233 |
| 0.0386        | 6.0   | 1170 | 0.0499          | 0.6141   | 0.6701 | 0.7151    | 0.6304 |
| 0.0386        | 7.0   | 1365 | 0.0503          | 0.6206   | 0.6754 | 0.7265    | 0.6310 |
| 0.0283        | 8.0   | 1560 | 0.0512          | 0.6199   | 0.6717 | 0.7129    | 0.6349 |
| 0.0283        | 9.0   | 1755 | 0.0515          | 0.6193   | 0.6720 | 0.7228    | 0.6278 |
| 0.0283        | 10.0  | 1950 | 0.0517          | 0.6283   | 0.6777 | 0.7292    | 0.6330 |


### Framework versions

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