---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: beomi/gemma-ko-7b
model-index:
- name: gemma7_on_korean_conv
  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_conv

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: 1.7037

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 5
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 7200

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8472        | 0.1281 | 200  | 0.8849          |
| 0.7799        | 0.2563 | 400  | 0.8185          |
| 0.7791        | 0.3844 | 600  | 0.7945          |
| 0.7505        | 0.5126 | 800  | 0.7877          |
| 0.7891        | 0.6407 | 1000 | 0.7616          |
| 0.689         | 0.7688 | 1200 | 0.7437          |
| 0.7612        | 0.8970 | 1400 | 0.7520          |
| 0.5183        | 1.0251 | 1600 | 0.8028          |
| 0.4562        | 1.1533 | 1800 | 0.7811          |
| 0.4584        | 1.2814 | 2000 | 0.7920          |
| 0.4535        | 1.4095 | 2200 | 0.7887          |
| 0.4268        | 1.5377 | 2400 | 0.8048          |
| 0.4368        | 1.6658 | 2600 | 0.7640          |
| 0.4435        | 1.7940 | 2800 | 0.7844          |
| 0.4327        | 1.9221 | 3000 | 0.7977          |
| 0.1711        | 2.0502 | 3200 | 1.0313          |
| 0.1856        | 2.1784 | 3400 | 0.9997          |
| 0.1812        | 2.3065 | 3600 | 0.9870          |
| 0.1876        | 2.4346 | 3800 | 0.9731          |
| 0.1927        | 2.5628 | 4000 | 0.9857          |
| 0.1964        | 2.6909 | 4200 | 1.0148          |
| 0.1948        | 2.8191 | 4400 | 1.0025          |
| 0.1865        | 2.9472 | 4600 | 1.0556          |
| 0.059         | 3.0753 | 4800 | 1.3127          |
| 0.0523        | 3.2035 | 5000 | 1.3947          |
| 0.0658        | 3.3316 | 5200 | 1.3980          |
| 0.0596        | 3.4598 | 5400 | 1.3785          |
| 0.0556        | 3.5879 | 5600 | 1.3936          |
| 0.0709        | 3.7160 | 5800 | 1.3858          |
| 0.0544        | 3.8442 | 6000 | 1.3943          |
| 0.0503        | 3.9723 | 6200 | 1.4319          |
| 0.0133        | 4.1005 | 6400 | 1.6485          |
| 0.0144        | 4.2286 | 6600 | 1.6932          |
| 0.0126        | 4.3567 | 6800 | 1.6980          |
| 0.0189        | 4.4849 | 7000 | 1.6962          |
| 0.0128        | 4.6130 | 7200 | 1.7037          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1