histoSwin-base
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the nctcrche100_k dataset. It achieves the following results on the evaluation set:
- Loss: 0.1260
- Accuracy: 0.9709
Model description
More information needed
Intended uses & limitations
For TMA classification.
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0386 | 1.0 | 1562 | 0.1740 | 0.9592 |
0.05 | 2.0 | 3125 | 0.2313 | 0.9524 |
0.0324 | 3.0 | 4687 | 0.2606 | 0.9604 |
0.005 | 4.0 | 6250 | 0.1724 | 0.9660 |
0.0037 | 5.0 | 7810 | 0.1260 | 0.9709 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for wangyk22/histoSwin-base
Base model
microsoft/swin-base-patch4-window7-224Evaluation results
- Accuracy on nctcrche100_kvalidation set self-reported0.971