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

# results

This model is a fine-tuned version of [tangminhanh/results](https://huggingface.co/tangminhanh/results) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0214
- Accuracy: 0.8673
- F1: 0.8828
- Precision: 0.8907
- Recall: 0.8750

## 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: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0959        | 1.0   | 816  | 0.0287          | 0.7330   | 0.7966 | 0.8666    | 0.7371 |
| 0.0223        | 2.0   | 1632 | 0.0203          | 0.8256   | 0.8587 | 0.8922    | 0.8277 |
| 0.0171        | 3.0   | 2448 | 0.0197          | 0.8348   | 0.8639 | 0.8824    | 0.8463 |
| 0.0116        | 4.0   | 3264 | 0.0194          | 0.8486   | 0.8708 | 0.8873    | 0.8548 |
| 0.0101        | 5.0   | 4080 | 0.0198          | 0.8532   | 0.8704 | 0.8798    | 0.8612 |
| 0.008         | 6.0   | 4896 | 0.0200          | 0.8550   | 0.8742 | 0.8872    | 0.8615 |
| 0.0065        | 7.0   | 5712 | 0.0204          | 0.8614   | 0.8775 | 0.8867    | 0.8686 |
| 0.0056        | 8.0   | 6528 | 0.0208          | 0.8587   | 0.8768 | 0.8858    | 0.8679 |
| 0.0048        | 9.0   | 7344 | 0.0214          | 0.8624   | 0.8781 | 0.8875    | 0.8689 |
| 0.0044        | 10.0  | 8160 | 0.0214          | 0.8673   | 0.8828 | 0.8907    | 0.8750 |


### Framework versions

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