---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi-3-vi-sft-1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# phi-3-vi-sft-1

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co./microsoft/Phi-3-mini-4k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0711

## Model description

Fine-tuning Phi-3-4b with Vietnamese Domain, VI_LIMA and VI_Alpaca Dataset

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 4
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4031        | 0.17  | 40   | 1.2004          |
| 1.1508        | 0.34  | 80   | 1.1312          |
| 1.1055        | 0.51  | 120  | 1.1002          |
| 1.0814        | 0.67  | 160  | 1.0820          |
| 1.0735        | 0.84  | 200  | 1.0711          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.2