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--- |
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base_model: rtzr/ko-gemma-2-9b-it |
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library_name: peft |
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license: gemma |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: gemma9_on_korean_summary_events |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gemma9_on_korean_summary_events |
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This model is a fine-tuned version of [rtzr/ko-gemma-2-9b-it](https://huggingface.co/rtzr/ko-gemma-2-9b-it) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4183 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 5 |
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- total_train_batch_size: 10 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 400 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.5952 | 0.1316 | 20 | 1.0820 | |
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| 0.9103 | 0.2632 | 40 | 0.7513 | |
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| 0.7022 | 0.3947 | 60 | 0.5833 | |
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| 0.5149 | 0.5263 | 80 | 0.4630 | |
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| 0.4837 | 0.6579 | 100 | 0.4376 | |
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| 0.449 | 0.7895 | 120 | 0.4213 | |
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| 0.431 | 0.9211 | 140 | 0.4080 | |
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| 0.3811 | 1.0526 | 160 | 0.4000 | |
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| 0.3227 | 1.1842 | 180 | 0.3964 | |
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| 0.283 | 1.3158 | 200 | 0.3974 | |
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| 0.2984 | 1.4474 | 220 | 0.3993 | |
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| 0.3102 | 1.5789 | 240 | 0.3851 | |
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| 0.3045 | 1.7105 | 260 | 0.3847 | |
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| 0.3034 | 1.8421 | 280 | 0.3851 | |
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| 0.2779 | 1.9737 | 300 | 0.3793 | |
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| 0.2191 | 2.1053 | 320 | 0.3991 | |
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| 0.1971 | 2.2368 | 340 | 0.4157 | |
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| 0.1908 | 2.3684 | 360 | 0.4209 | |
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| 0.1766 | 2.5 | 380 | 0.4190 | |
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| 0.1749 | 2.6316 | 400 | 0.4183 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
