---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: beomi/gemma-ko-2b
model-index:
- name: gemma2_on_korean_conv-base-stm
  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. -->

# gemma2_on_korean_conv-base-stm

This model is a fine-tuned version of [beomi/gemma-ko-2b](https://huggingface.co/beomi/gemma-ko-2b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1954

## 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: 10
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4804        | 0.2563 | 100  | 1.4702          |
| 1.3147        | 0.5126 | 200  | 1.3067          |
| 1.2424        | 0.7688 | 300  | 1.2374          |
| 1.0918        | 1.0251 | 400  | 1.1792          |
| 0.9923        | 1.2814 | 500  | 1.1563          |
| 0.9586        | 1.5377 | 600  | 1.1370          |
| 0.9639        | 1.7940 | 700  | 1.1093          |
| 0.7698        | 2.0502 | 800  | 1.1266          |
| 0.7274        | 2.3065 | 900  | 1.1393          |
| 0.7416        | 2.5628 | 1000 | 1.1022          |
| 0.759         | 2.8191 | 1100 | 1.0903          |
| 0.5755        | 3.0753 | 1200 | 1.1302          |
| 0.5839        | 3.3316 | 1300 | 1.1443          |
| 0.6008        | 3.5879 | 1400 | 1.1300          |
| 0.5773        | 3.8442 | 1500 | 1.1326          |
| 0.4565        | 4.1005 | 1600 | 1.1757          |
| 0.4436        | 4.3567 | 1700 | 1.1832          |
| 0.4462        | 4.6130 | 1800 | 1.1816          |
| 0.4502        | 4.8693 | 1900 | 1.1878          |
| 0.3731        | 5.1256 | 2000 | 1.1954          |


### Framework versions

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