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Dataset1-SwinV2
Nicole-M/Dataset1-SwinV2
Dataset1-SwinV2 is a image classification model from Nicole-M. Use it when you need a label for an image.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Model type
- swinv2
- Access
- Public
- Created
- Aug 13, 2024
- Updated
- Aug 21, 2024
- SHA
- 8df0b8c4
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Task
- Image Classification
- Type
- swinv2
- Created
- Aug 13, 2024
- Updated
- Aug 21, 2024