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organamnist-swin-base-finetuned
This model is a fine-tuned version of microsoft/swin-large-patch4-window7-224-in22k on the medmnist-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2521
- Accuracy: 0.9387
- Precision: 0.9430
- Recall: 0.9343
- F1: 0.9373
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: 0.005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.6172 | 1.0 | 540 | 0.1913 | 0.9373 | 0.9481 | 0.9427 | 0.9422 |
0.6346 | 2.0 | 1081 | 0.0756 | 0.9760 | 0.9799 | 0.9752 | 0.9770 |
0.6405 | 3.0 | 1621 | 0.1310 | 0.9553 | 0.9600 | 0.9515 | 0.9537 |
0.5005 | 4.0 | 2162 | 0.1138 | 0.9663 | 0.9757 | 0.9718 | 0.9729 |
0.5669 | 5.0 | 2702 | 0.1142 | 0.9603 | 0.9704 | 0.9647 | 0.9665 |
0.5548 | 6.0 | 3243 | 0.0569 | 0.9772 | 0.9812 | 0.9785 | 0.9795 |
0.4298 | 7.0 | 3783 | 0.0989 | 0.9663 | 0.9770 | 0.9723 | 0.9736 |
0.3932 | 8.0 | 4324 | 0.0335 | 0.9884 | 0.9903 | 0.9887 | 0.9894 |
0.3409 | 9.0 | 4864 | 0.0371 | 0.9878 | 0.9900 | 0.9877 | 0.9887 |
0.3111 | 9.99 | 5400 | 0.0433 | 0.9846 | 0.9888 | 0.9864 | 0.9874 |
Framework versions
- PEFT 0.11.1
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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