---
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
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 [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2168

## 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  | 1.7080          |
| 1.7499        | 2.0   | 694  | 1.6328          |
| 1.5826        | 3.0   | 1041 | 1.5591          |
| 1.5826        | 4.0   | 1388 | 1.5279          |
| 1.4058        | 5.0   | 1735 | 1.5295          |
| 1.2876        | 6.0   | 2082 | 1.4994          |
| 1.2876        | 7.0   | 2429 | 1.5424          |
| 1.1541        | 8.0   | 2776 | 1.5887          |
| 1.0159        | 9.0   | 3123 | 1.6156          |
| 1.0159        | 10.0  | 3470 | 1.6521          |
| 0.908         | 11.0  | 3817 | 1.7413          |
| 0.7714        | 12.0  | 4164 | 1.8127          |
| 0.6767        | 13.0  | 4511 | 1.8821          |
| 0.6767        | 14.0  | 4858 | 1.9855          |
| 0.5607        | 15.0  | 5205 | 2.0127          |
| 0.4934        | 16.0  | 5552 | 2.0784          |
| 0.4934        | 17.0  | 5899 | 2.1366          |
| 0.4446        | 18.0  | 6246 | 2.1425          |
| 0.3855        | 19.0  | 6593 | 2.1683          |
| 0.3855        | 20.0  | 6940 | 2.1682          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.4.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2