---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vietcuna-3b_2048
  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-3b_2048

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5250
- Accuracy: 0.7375

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.18
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5694        | 1.05  | 50   | 0.5834          | 0.7087   |
| 0.5614        | 2.1   | 100  | 0.5772          | 0.7165   |
| 0.5475        | 3.15  | 150  | 0.5684          | 0.7165   |
| 0.5503        | 4.2   | 200  | 0.5605          | 0.7087   |
| 0.5305        | 5.25  | 250  | 0.5784          | 0.7192   |
| 0.5353        | 6.3   | 300  | 0.5451          | 0.7323   |
| 0.5063        | 7.35  | 350  | 0.5441          | 0.7270   |
| 0.5141        | 8.4   | 400  | 0.5365          | 0.7244   |
| 0.5035        | 9.45  | 450  | 0.5354          | 0.7297   |
| 0.493         | 10.5  | 500  | 0.5322          | 0.7297   |
| 0.4763        | 11.55 | 550  | 0.5299          | 0.7375   |
| 0.5063        | 12.6  | 600  | 0.5295          | 0.7375   |
| 0.4787        | 13.65 | 650  | 0.5280          | 0.7297   |
| 0.4841        | 14.7  | 700  | 0.5266          | 0.7375   |
| 0.4732        | 15.75 | 750  | 0.5283          | 0.7297   |
| 0.4801        | 16.8  | 800  | 0.5259          | 0.7375   |
| 0.4651        | 17.85 | 850  | 0.5256          | 0.7375   |
| 0.4726        | 18.9  | 900  | 0.5260          | 0.7323   |
| 0.4758        | 19.95 | 950  | 0.5248          | 0.7375   |
| 0.4701        | 21.0  | 1000 | 0.5250          | 0.7375   |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1