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

# pd_subcate

This model is a fine-tuned version of [tangminhanh/pd_cate](https://huggingface.co/tangminhanh/pd_cate) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1790
- Accuracy: 0.4074
- F1: 0.4502
- Precision: 0.4817
- Recall: 0.4227

## 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: 64
- eval_batch_size: 64
- 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 42   | 0.1567          | 0.4058   | 0.4567 | 0.4946    | 0.4242 |
| No log        | 2.0   | 84   | 0.1583          | 0.3997   | 0.4503 | 0.4901    | 0.4165 |
| No log        | 3.0   | 126  | 0.1599          | 0.4058   | 0.4613 | 0.5055    | 0.4242 |
| No log        | 4.0   | 168  | 0.1636          | 0.4150   | 0.4596 | 0.4973    | 0.4273 |
| No log        | 5.0   | 210  | 0.1670          | 0.3936   | 0.4474 | 0.4874    | 0.4135 |
| No log        | 6.0   | 252  | 0.1682          | 0.4043   | 0.4507 | 0.4867    | 0.4196 |
| No log        | 7.0   | 294  | 0.1739          | 0.4089   | 0.4594 | 0.4888    | 0.4334 |
| No log        | 8.0   | 336  | 0.1790          | 0.4074   | 0.4502 | 0.4817    | 0.4227 |


### Framework versions

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