large-try Done
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: CocoRoF/KoModernBERT-large-mlm-v2
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tags:
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- generated_from_trainer
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model-index:
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- name: KoModernBERT-large-mlm-v3
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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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# KoModernBERT-large-mlm-v3
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This model is a fine-tuned version of [CocoRoF/KoModernBERT-large-mlm-v2](https://huggingface.co/CocoRoF/KoModernBERT-large-mlm-v2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3605
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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: 1e-06
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 32
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- total_train_batch_size: 1024
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- total_eval_batch_size: 32
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 97.07 | 0.0599 | 500 | 3.0658 |
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| 97.6329 | 0.1199 | 1000 | 3.0890 |
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| 94.2036 | 0.1798 | 1500 | 2.9848 |
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| 93.88 | 0.2397 | 2000 | 2.8945 |
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| 91.2063 | 0.2997 | 2500 | 2.8105 |
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| 88.1768 | 0.3596 | 3000 | 2.7460 |
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| 86.8633 | 0.4196 | 3500 | 2.6891 |
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| 84.4198 | 0.4795 | 4000 | 2.6377 |
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| 81.6633 | 0.5394 | 4500 | 2.5888 |
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| 81.2498 | 0.5994 | 5000 | 2.5427 |
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| 79.082 | 0.6593 | 5500 | 2.5001 |
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| 78.3493 | 0.7192 | 6000 | 2.4693 |
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| 77.7304 | 0.7792 | 6500 | 2.4339 |
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| 77.1332 | 0.8391 | 7000 | 2.4003 |
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| 75.6454 | 0.8990 | 7500 | 2.3795 |
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| 74.7334 | 0.9590 | 8000 | 2.3605 |
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.3.2
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- Tokenizers 0.21.1
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