mobilevit_ai_real_classifier
This model is a fine-tuned version of apple/mobilevit-small on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1279
- Accuracy: 0.9567
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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2617 | 1.0 | 219 | 0.2093 | 0.918 |
| 0.2115 | 2.0 | 438 | 0.1867 | 0.921 |
| 0.1832 | 3.0 | 657 | 0.2291 | 0.9135 |
| 0.1516 | 4.0 | 876 | 0.1993 | 0.9175 |
| 0.1303 | 5.0 | 1095 | 0.1567 | 0.945 |
| 0.1113 | 6.0 | 1314 | 0.1590 | 0.947 |
| 0.0992 | 7.0 | 1533 | 0.1634 | 0.94 |
| 0.0794 | 8.0 | 1752 | 0.1702 | 0.9445 |
| 0.0819 | 9.0 | 1971 | 0.1566 | 0.949 |
| 0.0725 | 10.0 | 2190 | 0.1620 | 0.949 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for songthienll/mobilevit_ai_real_classifier
Base model
apple/mobilevit-smallEvaluation results
- Accuracy on imagefolderself-reported0.957