---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: beomi/gemma-ko-7b
model-index:
- name: gemma7_on_korean_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. -->

# gemma7_on_korean_events

This model is a fine-tuned version of [beomi/gemma-ko-7b](https://huggingface.co/beomi/gemma-ko-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5534

## 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: 760
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0063        | 0.2632 | 20   | 0.6860          |
| 0.4681        | 0.5263 | 40   | 0.3754          |
| 0.3565        | 0.7895 | 60   | 0.3030          |
| 0.2872        | 1.0526 | 80   | 0.2880          |
| 0.2557        | 1.3158 | 100  | 0.2723          |
| 0.2213        | 1.5789 | 120  | 0.2674          |
| 0.2386        | 1.8421 | 140  | 0.2537          |
| 0.1885        | 2.1053 | 160  | 0.3032          |
| 0.1362        | 2.3684 | 180  | 0.2710          |
| 0.131         | 2.6316 | 200  | 0.2844          |
| 0.1366        | 2.8947 | 220  | 0.2626          |
| 0.0935        | 3.1579 | 240  | 0.3632          |
| 0.0618        | 3.4211 | 260  | 0.3315          |
| 0.0672        | 3.6842 | 280  | 0.3255          |
| 0.0684        | 3.9474 | 300  | 0.3238          |
| 0.0393        | 4.2105 | 320  | 0.4230          |
| 0.0311        | 4.4737 | 340  | 0.4180          |
| 0.0337        | 4.7368 | 360  | 0.3933          |
| 0.0402        | 5.0    | 380  | 0.3846          |
| 0.0179        | 5.2632 | 400  | 0.4478          |
| 0.0176        | 5.5263 | 420  | 0.4464          |
| 0.0274        | 5.7895 | 440  | 0.4003          |
| 0.017         | 6.0526 | 460  | 0.4284          |
| 0.0112        | 6.3158 | 480  | 0.4675          |
| 0.0107        | 6.5789 | 500  | 0.4715          |
| 0.0115        | 6.8421 | 520  | 0.4911          |
| 0.0107        | 7.1053 | 540  | 0.4776          |
| 0.0053        | 7.3684 | 560  | 0.4829          |
| 0.0049        | 7.6316 | 580  | 0.4962          |
| 0.0046        | 7.8947 | 600  | 0.5087          |
| 0.0039        | 8.1579 | 620  | 0.5240          |
| 0.0028        | 8.4211 | 640  | 0.5317          |
| 0.0035        | 8.6842 | 660  | 0.5351          |
| 0.0034        | 8.9474 | 680  | 0.5393          |
| 0.0013        | 9.2105 | 700  | 0.5445          |
| 0.0031        | 9.4737 | 720  | 0.5502          |
| 0.0018        | 9.7368 | 740  | 0.5523          |
| 0.002         | 10.0   | 760  | 0.5534          |


### Framework versions

- PEFT 0.11.2.dev0
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1