metadata
library_name: transformers
license: mit
base_model: Yuvrajg2107/deberta-v3-hybrid-detector_12
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-hybrid-detector_v2_universal
results: []
deberta-v3-hybrid-detector_v2_universal
This model is a fine-tuned version of Yuvrajg2107/deberta-v3-hybrid-detector_12 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0389
- Accuracy: 0.9631
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-06
- train_batch_size: 8
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.0127 | 0.1455 | 1000 | 0.0275 | 0.9659 |
| 0.0083 | 0.2909 | 2000 | 0.0469 | 0.9541 |
| 0.0065 | 0.4364 | 3000 | 0.0439 | 0.9544 |
| 0.0063 | 0.5818 | 4000 | 0.0207 | 0.9785 |
| 0.007 | 0.7273 | 5000 | 0.0342 | 0.9647 |
| 0.0046 | 0.8727 | 6000 | 0.0389 | 0.9631 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.6.0+cu124
- Datasets 4.4.2
- Tokenizers 0.22.1