vit-base-brain-mri
This model is a fine-tuned version of google/vit-base-patch16-224 on the BrainMRI dataset. It achieves the following results on the evaluation set:
- Loss: 1.0577
- Accuracy: 0.5990
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 72 | 0.9986 | 0.6098 |
| 1.098 | 2.0 | 144 | 0.8445 | 0.7003 |
| 0.7895 | 3.0 | 216 | 0.7318 | 0.7526 |
| 0.7895 | 4.0 | 288 | 0.6842 | 0.7474 |
| 0.6629 | 5.0 | 360 | 0.6328 | 0.7857 |
| 0.5966 | 6.0 | 432 | 0.5957 | 0.8101 |
| 0.5546 | 7.0 | 504 | 0.5646 | 0.8118 |
| 0.5546 | 8.0 | 576 | 0.5647 | 0.8049 |
| 0.5113 | 9.0 | 648 | 0.5340 | 0.8275 |
| 0.4882 | 10.0 | 720 | 0.5190 | 0.8328 |
| 0.4882 | 11.0 | 792 | 0.5197 | 0.8328 |
| 0.4789 | 12.0 | 864 | 0.5002 | 0.8258 |
| 0.4582 | 13.0 | 936 | 0.4957 | 0.8310 |
| 0.4426 | 14.0 | 1008 | 0.4821 | 0.8310 |
| 0.4426 | 15.0 | 1080 | 0.4706 | 0.8467 |
| 0.4328 | 16.0 | 1152 | 0.4821 | 0.8153 |
| 0.432 | 17.0 | 1224 | 0.4992 | 0.8275 |
| 0.432 | 18.0 | 1296 | 0.4799 | 0.8345 |
| 0.4196 | 19.0 | 1368 | 0.4838 | 0.8310 |
| 0.4287 | 20.0 | 1440 | 0.4598 | 0.8659 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1