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ai_vs_human_detector_deberta_v3_robust
XOmar/ai_vs_human_detector_deberta_v3_robust
ai_vs_human_detector_deberta_v3_robust is a text classification model from XOmar. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Dec 5, 2025
- Updated
- Dec 5, 2025
- SHA
- 76ec51a0
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
ai_vs_human_detector_deberta_v3_robust
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0228
- Accuracy: 0.9940
- F1: 0.9939
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1372 | 0.1082 | 500 | 0.0982 | 0.9631 | 0.9638 |
| 0.0362 | 0.2164 | 1000 | 0.0379 | 0.9891 | 0.9890 |
| 0.037 | 0.3246 | 1500 | 0.0409 | 0.9884 | 0.9884 |
| 0.0325 | 0.4328 | 2000 | 0.0287 | 0.9919 | 0.9918 |
| 0.0222 | 0.5410 | 2500 | 0.0262 | 0.9943 | 0.9943 |
| 0.0222 | 0.6492 | 3000 | 0.0209 | 0.9945 | 0.9944 |
| 0.0218 | 0.7575 | 3500 | 0.0494 | 0.9879 | 0.9879 |
| 0.019 | 0.8657 | 4000 | 0.0198 | 0.9950 | 0.9949 |
| 0.0226 | 0.9739 | 4500 | 0.0228 | 0.9940 | 0.9939 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.7.1+cu118
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Dec 5, 2025
- Updated
- Dec 5, 2025