vit-msn-small-corect_deepcleaned_dataset_lateral_flow_ivalidation
This model is a fine-tuned version of facebook/vit-msn-small on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2229
- Accuracy: 0.9194
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9231 | 3 | 0.6175 | 0.7216 |
| No log | 1.8462 | 6 | 0.4141 | 0.8352 |
| No log | 2.7692 | 9 | 0.7408 | 0.5788 |
| 0.5817 | 4.0 | 13 | 0.2757 | 0.9158 |
| 0.5817 | 4.9231 | 16 | 0.2847 | 0.8791 |
| 0.5817 | 5.8462 | 19 | 0.2456 | 0.9011 |
| 0.3724 | 6.7692 | 22 | 0.2547 | 0.9121 |
| 0.3724 | 8.0 | 26 | 0.3007 | 0.8828 |
| 0.3724 | 8.9231 | 29 | 0.3043 | 0.9011 |
| 0.3155 | 9.8462 | 32 | 0.2603 | 0.9048 |
| 0.3155 | 10.7692 | 35 | 0.2481 | 0.9158 |
| 0.3155 | 12.0 | 39 | 0.2229 | 0.9194 |
| 0.2844 | 12.9231 | 42 | 0.3036 | 0.8791 |
| 0.2844 | 13.8462 | 45 | 0.2579 | 0.9084 |
| 0.2844 | 14.7692 | 48 | 0.2434 | 0.9158 |
| 0.2517 | 16.0 | 52 | 0.2718 | 0.9048 |
| 0.2517 | 16.9231 | 55 | 0.2513 | 0.9121 |
| 0.2517 | 17.8462 | 58 | 0.2503 | 0.9121 |
| 0.2468 | 18.4615 | 60 | 0.2491 | 0.9121 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1