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--- |
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library_name: transformers |
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base_model: yangwooko/smartmind-cyberone-20250405 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: smartmind-cyberone-20250507-0420-revisit |
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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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# smartmind-cyberone-20250507-0420-revisit |
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This model is a fine-tuned version of [yangwooko/smartmind-cyberone-20250405](https://huggingface.co/yangwooko/smartmind-cyberone-20250405) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0135 |
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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: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 4096 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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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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| 0.0153 | 0.3527 | 30 | 0.0180 | |
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| 0.0161 | 0.7054 | 60 | 0.0312 | |
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| 0.0207 | 1.0470 | 90 | 0.0364 | |
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| 0.0285 | 1.3997 | 120 | 0.0227 | |
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| 0.0211 | 1.7524 | 150 | 0.0218 | |
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| 0.0161 | 2.0940 | 180 | 0.0202 | |
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| 0.0174 | 2.4467 | 210 | 0.0197 | |
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| 0.017 | 2.7994 | 240 | 0.0202 | |
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| 0.0151 | 3.1411 | 270 | 0.0160 | |
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| 0.016 | 3.4938 | 300 | 0.0129 | |
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| 0.0162 | 3.8464 | 330 | 0.0134 | |
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| 0.0157 | 4.1881 | 360 | 0.0132 | |
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| 0.0156 | 4.5408 | 390 | 0.0144 | |
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| 0.015 | 4.8935 | 420 | 0.0135 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.7.0+cu126 |
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- Tokenizers 0.21.1 |
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