---
base_model: vilm/vietcuna-7b-v3
tags:
- generated_from_trainer
model-index:
- name: vietcuna-7b-test-exam-12
  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. -->

# vietcuna-7b-test-exam-12

This model is a fine-tuned version of [vilm/vietcuna-7b-v3](https://huggingface.co/vilm/vietcuna-7b-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7656

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 14.3516       | 0.15  | 300  | 13.9922         |
| 10.0687       | 0.31  | 600  | 9.3828          |
| 7.2003        | 0.46  | 900  | 6.9414          |
| 6.0928        | 0.61  | 1200 | 5.9883          |
| 5.6407        | 0.77  | 1500 | 5.6133          |
| 5.4097        | 0.92  | 1800 | 5.375           |
| 5.2841        | 1.07  | 2100 | 5.2305          |
| 5.1691        | 1.23  | 2400 | 5.1875          |
| 5.0585        | 1.38  | 2700 | 5.0664          |
| 4.9741        | 1.53  | 3000 | 5.0078          |
| 4.9581        | 1.69  | 3300 | 4.9531          |
| 4.9653        | 1.84  | 3600 | 4.9102          |
| 4.8763        | 1.99  | 3900 | 4.8711          |
| 4.8308        | 2.15  | 4200 | 4.8281          |
| 4.7993        | 2.3   | 4500 | 4.8125          |
| 4.8228        | 2.46  | 4800 | 4.8047          |
| 4.789         | 2.61  | 5100 | 4.7852          |
| 4.8048        | 2.76  | 5400 | 4.7734          |
| 4.7566        | 2.92  | 5700 | 4.7656          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.14.1