retinal_disease_model
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8147
- Accuracy: 0.6062
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5345 | 1.0 | 293 | 1.3042 | 0.3991 |
| 1.2525 | 2.0 | 586 | 1.3418 | 0.3633 |
| 1.0851 | 3.0 | 879 | 1.2063 | 0.5008 |
| 0.9413 | 4.0 | 1172 | 1.0855 | 0.4971 |
| 0.8212 | 5.0 | 1465 | 0.9673 | 0.4848 |
| 0.7118 | 6.0 | 1758 | 0.9683 | 0.5350 |
| 0.6451 | 7.0 | 2051 | 0.8728 | 0.6009 |
| 0.5910 | 8.0 | 2344 | 0.8177 | 0.5939 |
| 0.5518 | 9.0 | 2637 | 0.8230 | 0.5993 |
| 0.5383 | 10.0 | 2930 | 0.8147 | 0.6062 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for eliasteikari/retinal_disease_model
Base model
google/vit-base-patch16-224