ai-detect-3
This model is a fine-tuned version of akshayvkt/detect-ai-text-1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3991
- Accuracy: 0.9297
- Precision: 0.9232
- Recall: 0.9682
- F1: 0.9452
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.1662 | 1.0 | 6250 | 0.1980 | 0.9205 | 0.9117 | 0.9666 | 0.9383 |
0.1581 | 2.0 | 12500 | 0.4775 | 0.8741 | 0.8439 | 0.9802 | 0.9069 |
0.0662 | 3.0 | 18750 | 0.4612 | 0.9031 | 0.8739 | 0.9877 | 0.9273 |
0.0112 | 4.0 | 25000 | 0.3991 | 0.9297 | 0.9232 | 0.9682 | 0.9452 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for mekjr1/ai-detect-3
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distilbert/distilbert-base-uncased
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akshayvkt/detect-ai-text-1