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--- |
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license: mit |
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base_model: openai-community/roberta-large-openai-detector |
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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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- recall |
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- precision |
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- f1 |
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model-index: |
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- name: openai-roberta-large-AI-detection |
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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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# openai-roberta-large-AI-detection |
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This model is a fine-tuned version of [openai-community/roberta-large-openai-detector](https://huggingface.co/openai-community/roberta-large-openai-detector) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5761 |
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- Accuracy: 0.7308 |
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- Recall: 0.7513 |
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- Precision: 0.7595 |
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- F1: 0.7554 |
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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 | Recall | Precision | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.6973 | 1.0 | 197 | 0.5936 | 0.7071 | 0.9652 | 0.6612 | 0.7848 | |
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| 0.658 | 2.0 | 394 | 0.5761 | 0.7308 | 0.7513 | 0.7595 | 0.7554 | |
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| 0.4746 | 3.0 | 591 | 0.6044 | 0.7071 | 0.8690 | 0.6857 | 0.7665 | |
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| 0.3514 | 4.0 | 788 | 0.7278 | 0.7293 | 0.8636 | 0.7099 | 0.7793 | |
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| 0.2263 | 5.0 | 985 | 1.2186 | 0.7071 | 0.8636 | 0.6872 | 0.7654 | |
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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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