---
library_name: peft
base_model: Korabbit/llama-2-ko-7b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 2493e57b-de64-4dd4-b986-1eff20f15fa3
  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>

# 2493e57b-de64-4dd4-b986-1eff20f15fa3

This model is a fine-tuned version of [Korabbit/llama-2-ko-7b](https://huggingface.co/Korabbit/llama-2-ko-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5627

## 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: 0.000214
- train_batch_size: 4
- eval_batch_size: 4
- seed: 140
- 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        | 0.0005 | 1    | 1.1167          |
| 0.5741        | 0.0258 | 50   | 0.6580          |
| 0.5458        | 0.0516 | 100  | 0.6708          |
| 0.541         | 0.0774 | 150  | 0.6404          |
| 0.5495        | 0.1033 | 200  | 0.6214          |
| 0.5433        | 0.1291 | 250  | 0.6066          |
| 0.5177        | 0.1549 | 300  | 0.5884          |
| 0.535         | 0.1807 | 350  | 0.5746          |
| 0.4859        | 0.2065 | 400  | 0.5650          |
| 0.4975        | 0.2323 | 450  | 0.5632          |
| 0.4496        | 0.2581 | 500  | 0.5627          |


### Framework versions

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