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--- |
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metrics: |
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- f1 |
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model-index: |
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- name: curse_classification |
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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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# curse_classification |
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This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2780 |
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- Precision: 0.8727 |
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- Recall: 0.8752 |
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- F1: 0.8739 |
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- Accuracy: 0.8835 |
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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: 128 |
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- eval_batch_size: 64 |
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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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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.3511 | 1.0 | 618 | 0.2939 | 0.8532 | 0.8591 | 0.8561 | 0.8720 | |
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| 0.2546 | 2.0 | 1236 | 0.2924 | 0.8721 | 0.8552 | 0.8636 | 0.8802 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
