---
library_name: peft
license: llama3
base_model: MLP-KTLim/llama-3-Korean-Bllossom-8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: e93d50ea-7420-4148-8bc1-2c4ecbdc2835
  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>

# e93d50ea-7420-4148-8bc1-2c4ecbdc2835

This model is a fine-tuned version of [MLP-KTLim/llama-3-Korean-Bllossom-8B](https://huggingface.co/MLP-KTLim/llama-3-Korean-Bllossom-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3223

## 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: 0.000212
- train_batch_size: 4
- eval_batch_size: 4
- seed: 120
- 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    | 1.9441          |
| 0.895         | 0.0456 | 50   | 0.9801          |
| 0.7945        | 0.0912 | 100  | 0.8731          |
| 0.6886        | 0.1369 | 150  | 0.8619          |
| 0.7819        | 0.1825 | 200  | 0.7114          |
| 0.6048        | 0.2281 | 250  | 0.5683          |
| 0.503         | 0.2737 | 300  | 0.5383          |
| 0.4986        | 0.3193 | 350  | 0.4003          |
| 0.5244        | 0.3650 | 400  | 0.3518          |
| 0.5655        | 0.4106 | 450  | 0.3261          |
| 0.4691        | 0.4562 | 500  | 0.3223          |


### Framework versions

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