---
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: DACN3_LVC
  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. -->

# DACN3_LVC

This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6146

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 347  | 1.1922          |
| 1.3869        | 2.0   | 694  | 1.0903          |
| 0.893         | 3.0   | 1041 | 1.0290          |
| 0.893         | 4.0   | 1388 | 1.0825          |
| 0.5968        | 5.0   | 1735 | 1.2634          |
| 0.4001        | 6.0   | 2082 | 1.4108          |
| 0.4001        | 7.0   | 2429 | 1.5288          |
| 0.2505        | 8.0   | 2776 | 1.6623          |
| 0.1639        | 9.0   | 3123 | 1.8938          |
| 0.1639        | 10.0  | 3470 | 2.0609          |
| 0.1143        | 11.0  | 3817 | 2.2725          |
| 0.0739        | 12.0  | 4164 | 2.4275          |
| 0.0552        | 13.0  | 4511 | 2.4773          |
| 0.0552        | 14.0  | 4858 | 2.5629          |
| 0.0389        | 15.0  | 5205 | 2.6769          |
| 0.029         | 16.0  | 5552 | 2.7282          |
| 0.029         | 17.0  | 5899 | 2.7699          |
| 0.0176        | 18.0  | 6246 | 2.7834          |
| 0.0171        | 19.0  | 6593 | 2.8041          |
| 0.0171        | 20.0  | 6940 | 2.7942          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.5.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2