gemma2_on_korean_conv-stm
This model is a fine-tuned version of beomi/gemma-ko-2b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1996
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 |
---|---|---|---|
1.4813 | 0.2563 | 100 | 1.4715 |
1.3177 | 0.5126 | 200 | 1.3092 |
1.2445 | 0.7688 | 300 | 1.2380 |
1.0947 | 1.0251 | 400 | 1.1796 |
0.996 | 1.2814 | 500 | 1.1585 |
0.9617 | 1.5377 | 600 | 1.1360 |
0.9645 | 1.7940 | 700 | 1.1112 |
0.7718 | 2.0502 | 800 | 1.1270 |
0.7281 | 2.3065 | 900 | 1.1372 |
0.7437 | 2.5628 | 1000 | 1.1040 |
0.7588 | 2.8191 | 1100 | 1.0921 |
0.5759 | 3.0753 | 1200 | 1.1330 |
0.5811 | 3.3316 | 1300 | 1.1485 |
0.6025 | 3.5879 | 1400 | 1.1298 |
0.5766 | 3.8442 | 1500 | 1.1391 |
0.4555 | 4.1005 | 1600 | 1.1785 |
0.4426 | 4.3567 | 1700 | 1.1874 |
0.4461 | 4.6130 | 1800 | 1.1865 |
0.4506 | 4.8693 | 1900 | 1.1902 |
0.3731 | 5.1256 | 2000 | 1.1996 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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