---
base_model: rtzr/ko-gemma-2-9b-it
library_name: peft
license: gemma
tags:
- generated_from_trainer
model-index:
- name: gemma9_on_korean_summary_events
  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. -->

# gemma9_on_korean_summary_events

This model is a fine-tuned version of [rtzr/ko-gemma-2-9b-it](https://huggingface.co/rtzr/ko-gemma-2-9b-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4183

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.5952        | 0.1316 | 20   | 1.0820          |
| 0.9103        | 0.2632 | 40   | 0.7513          |
| 0.7022        | 0.3947 | 60   | 0.5833          |
| 0.5149        | 0.5263 | 80   | 0.4630          |
| 0.4837        | 0.6579 | 100  | 0.4376          |
| 0.449         | 0.7895 | 120  | 0.4213          |
| 0.431         | 0.9211 | 140  | 0.4080          |
| 0.3811        | 1.0526 | 160  | 0.4000          |
| 0.3227        | 1.1842 | 180  | 0.3964          |
| 0.283         | 1.3158 | 200  | 0.3974          |
| 0.2984        | 1.4474 | 220  | 0.3993          |
| 0.3102        | 1.5789 | 240  | 0.3851          |
| 0.3045        | 1.7105 | 260  | 0.3847          |
| 0.3034        | 1.8421 | 280  | 0.3851          |
| 0.2779        | 1.9737 | 300  | 0.3793          |
| 0.2191        | 2.1053 | 320  | 0.3991          |
| 0.1971        | 2.2368 | 340  | 0.4157          |
| 0.1908        | 2.3684 | 360  | 0.4209          |
| 0.1766        | 2.5    | 380  | 0.4190          |
| 0.1749        | 2.6316 | 400  | 0.4183          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1