metadata
base_model: swinv2
tags:
- image-classification
- breast cancer
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: swinV2-Mammmogram-V1
results: []
swinV2-Mammmogram-V1
This model is a fine-tuned version of swinv2 on the Mammogram V1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1434
- Accuracy: 0.9524
- Precision: 0.9751
- Recall: 0.9524
- F1: 0.9630
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4455 | 1.0 | 1112 | 0.1385 | 0.9782 | 0.9739 | 0.9782 | 0.9760 |
| 0.3974 | 2.0 | 2224 | 0.1974 | 0.9524 | 0.9749 | 0.9524 | 0.9630 |
| 0.3712 | 3.0 | 3336 | 0.1386 | 0.9735 | 0.9748 | 0.9735 | 0.9741 |
| 0.2748 | 4.0 | 4448 | 0.1597 | 0.9479 | 0.9752 | 0.9479 | 0.9607 |
| 0.2603 | 5.0 | 5560 | 0.1434 | 0.9524 | 0.9751 | 0.9524 | 0.9630 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1