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