---
library_name: peft
base_model: oopsung/llama2-7b-koNqa-test-v1
tags:
- axolotl
- generated_from_trainer
model-index:
- name: f23ddbfa-4c23-4721-aebf-9cb2ee403b26
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# f23ddbfa-4c23-4721-aebf-9cb2ee403b26

This model is a fine-tuned version of [oopsung/llama2-7b-koNqa-test-v1](https://huggingface.co/oopsung/llama2-7b-koNqa-test-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1446

## 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: 0.000203
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0009 | 1    | 2.8770          |
| 0.4286        | 0.0443 | 50   | 0.4995          |
| 0.2728        | 0.0887 | 100  | 0.3726          |
| 0.2133        | 0.1330 | 150  | 0.3219          |
| 0.1883        | 0.1774 | 200  | 0.3201          |
| 0.1816        | 0.2217 | 250  | 0.2695          |
| 0.154         | 0.2661 | 300  | 0.2293          |
| 0.1834        | 0.3104 | 350  | 0.1767          |
| 0.1462        | 0.3548 | 400  | 0.1565          |
| 0.1159        | 0.3991 | 450  | 0.1439          |
| 0.0985        | 0.4435 | 500  | 0.1446          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1