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---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: beomi/gemma-ko-2b
model-index:
- name: gemma2_on_korean_summary
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_summary
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: 0.9622
## 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: 800
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6606 | 0.26 | 20 | 1.5454 |
| 1.4381 | 0.53 | 40 | 1.3247 |
| 1.2548 | 0.79 | 60 | 1.1921 |
| 1.1574 | 1.05 | 80 | 1.1227 |
| 1.0968 | 1.32 | 100 | 1.0727 |
| 1.0485 | 1.58 | 120 | 1.0316 |
| 1.0258 | 1.84 | 140 | 1.0019 |
| 0.9582 | 2.11 | 160 | 0.9785 |
| 0.906 | 2.37 | 180 | 0.9575 |
| 0.8837 | 2.63 | 200 | 0.9429 |
| 0.8763 | 2.89 | 220 | 0.9247 |
| 0.8295 | 3.16 | 240 | 0.9213 |
| 0.7799 | 3.42 | 260 | 0.9122 |
| 0.7742 | 3.68 | 280 | 0.8992 |
| 0.7708 | 3.95 | 300 | 0.8918 |
| 0.7196 | 4.21 | 320 | 0.8952 |
| 0.6908 | 4.47 | 340 | 0.8917 |
| 0.6977 | 4.74 | 360 | 0.8841 |
| 0.6789 | 5.0 | 380 | 0.8764 |
| 0.6198 | 5.26 | 400 | 0.9003 |
| 0.6203 | 5.53 | 420 | 0.9030 |
| 0.6169 | 5.79 | 440 | 0.8913 |
| 0.6111 | 6.05 | 460 | 0.8935 |
| 0.564 | 6.32 | 480 | 0.9096 |
| 0.5819 | 6.58 | 500 | 0.9027 |
| 0.5673 | 6.84 | 520 | 0.8997 |
| 0.5382 | 7.11 | 540 | 0.9181 |
| 0.5228 | 7.37 | 560 | 0.9197 |
| 0.5197 | 7.63 | 580 | 0.9254 |
| 0.5319 | 7.89 | 600 | 0.9158 |
| 0.4954 | 8.16 | 620 | 0.9394 |
| 0.4954 | 8.42 | 640 | 0.9345 |
| 0.4719 | 8.68 | 660 | 0.9388 |
| 0.4866 | 8.95 | 680 | 0.9390 |
| 0.4739 | 9.21 | 700 | 0.9528 |
| 0.4591 | 9.47 | 720 | 0.9534 |
| 0.4478 | 9.74 | 740 | 0.9542 |
| 0.4547 | 10.0 | 760 | 0.9539 |
| 0.4379 | 10.26 | 780 | 0.9617 |
| 0.4348 | 10.53 | 800 | 0.9622 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.0 |