openai-roberta-large-AI-detection
This model is a fine-tuned version of openai-community/roberta-large-openai-detector on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5761
- Accuracy: 0.7308
- Recall: 0.7513
- Precision: 0.7595
- F1: 0.7554
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 0.6973 | 1.0 | 197 | 0.5936 | 0.7071 | 0.9652 | 0.6612 | 0.7848 |
| 0.658 | 2.0 | 394 | 0.5761 | 0.7308 | 0.7513 | 0.7595 | 0.7554 |
| 0.4746 | 3.0 | 591 | 0.6044 | 0.7071 | 0.8690 | 0.6857 | 0.7665 |
| 0.3514 | 4.0 | 788 | 0.7278 | 0.7293 | 0.8636 | 0.7099 | 0.7793 |
| 0.2263 | 5.0 | 985 | 1.2186 | 0.7071 | 0.8636 | 0.6872 | 0.7654 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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