google-efficientnet-b3-finetuned-kidney_v4
This model is a fine-tuned version of google/efficientnet-b3 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2574
- Accuracy: 0.8965
- F1: 0.8941
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.5504 | 1.0 | 734 | 0.3980 | 0.8733 | 0.8720 |
| 2.1004 | 2.0 | 1468 | 0.3436 | 0.8794 | 0.8766 |
| 1.9085 | 3.0 | 2202 | 0.4911 | 0.8243 | 0.8186 |
| 2.1986 | 4.0 | 2936 | 0.2574 | 0.8965 | 0.8941 |
| 1.4978 | 5.0 | 3670 | 0.2788 | 0.8883 | 0.8806 |
| 1.2625 | 6.0 | 4404 | 0.2969 | 0.8937 | 0.8935 |
| 1.2516 | 7.0 | 5138 | 0.2742 | 0.8931 | 0.8884 |
| 1.2393 | 8.0 | 5872 | 0.7633 | 0.6846 | 0.6681 |
| 1.3415 | 9.0 | 6606 | 0.2815 | 0.8828 | 0.8752 |
| 1.4996 | 10.0 | 7340 | 0.2399 | 0.8965 | 0.8917 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2