---
library_name: peft
base_model: Korabbit/llama-2-ko-7b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 6b0f310e-8dfe-4d77-ab87-585c355ba4ee
  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>

# 6b0f310e-8dfe-4d77-ab87-585c355ba4ee

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: 0.8646

## 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: 0.000218
- 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        | 0.0001 | 1    | 1.3929          |
| 0.9803        | 0.0047 | 50   | 1.0977          |
| 0.7452        | 0.0094 | 100  | 1.0563          |
| 0.8894        | 0.0142 | 150  | 1.0474          |
| 0.878         | 0.0189 | 200  | 1.0044          |
| 0.8014        | 0.0236 | 250  | 0.9554          |
| 0.7658        | 0.0283 | 300  | 0.9113          |
| 0.6401        | 0.0331 | 350  | 0.8867          |
| 0.7264        | 0.0378 | 400  | 0.8729          |
| 0.7121        | 0.0425 | 450  | 0.8641          |
| 0.7067        | 0.0472 | 500  | 0.8646          |


### Framework versions

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