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--- |
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base_model: klue/roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: cosmetic3_roberta |
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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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# cosmetic3_roberta |
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This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3549 |
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- Accuracy: 0.8520 |
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- F1: 0.8563 |
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- Precision: 0.8640 |
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- Recall: 0.8526 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 500 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.4186 | 1.0 | 277 | 0.2708 | 0.8877 | 0.8911 | 0.8933 | 0.8897 | |
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| 0.3237 | 2.0 | 554 | 0.4175 | 0.8623 | 0.8624 | 0.8755 | 0.8727 | |
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| 0.2054 | 3.0 | 831 | 0.4479 | 0.8986 | 0.9008 | 0.9087 | 0.9055 | |
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| 0.3151 | 4.0 | 1108 | 0.3885 | 0.9130 | 0.9154 | 0.9163 | 0.9173 | |
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| 0.1832 | 5.0 | 1385 | 0.4418 | 0.9094 | 0.9120 | 0.9122 | 0.9132 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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