resnet-pretrained-brain-mri
This model is a fine-tuned version of microsoft/resnet-50 on the BrainMRI dataset. It achieves the following results on the evaluation set:
- Loss: 1.1450
- Accuracy: 0.5228
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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| No log | 1.0 | 72 | 0.4704 | 1.2440 |
| 1.2771 | 2.0 | 144 | 0.5575 | 1.1610 |
| 1.1543 | 3.0 | 216 | 0.6446 | 1.0949 |
| 1.1543 | 4.0 | 288 | 0.6812 | 1.0361 |
| 1.0664 | 5.0 | 360 | 0.6742 | 1.0100 |
| 0.9998 | 6.0 | 432 | 0.7003 | 0.9687 |
| 0.9537 | 7.0 | 504 | 0.6986 | 0.9484 |
| 0.9537 | 8.0 | 576 | 0.6934 | 0.9285 |
| 0.9239 | 9.0 | 648 | 0.7108 | 0.8992 |
| 0.893 | 10.0 | 720 | 0.7369 | 0.8723 |
| 0.893 | 11.0 | 792 | 0.7334 | 0.8635 |
| 0.8726 | 12.0 | 864 | 0.7474 | 0.8589 |
| 0.8482 | 13.0 | 936 | 0.7160 | 0.8423 |
| 0.8461 | 14.0 | 1008 | 0.7300 | 0.8481 |
| 0.8461 | 15.0 | 1080 | 0.7352 | 0.8312 |
| 0.8267 | 16.0 | 1152 | 0.7247 | 0.8319 |
| 0.8163 | 17.0 | 1224 | 0.7456 | 0.8136 |
| 0.8163 | 18.0 | 1296 | 0.7474 | 0.8151 |
| 0.8126 | 19.0 | 1368 | 0.7596 | 0.8071 |
| 0.8022 | 20.0 | 1440 | 0.7491 | 0.8210 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1
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Base model
microsoft/resnet-50