Upload Twins_SVT model from experiment b1
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- .gitattributes +2 -0
- README.md +161 -0
- config.json +76 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_a.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_b.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_c.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_d.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_e.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_f.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_g.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_h.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_i.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_j.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_k.png +0 -0
- confusion_matrices/Twins_SVT_Confusion_Matrix_l.png +0 -0
- evaluation_results.csv +133 -0
- model.safetensors +3 -0
- pytorch_model.bin +3 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_a.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_b.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_c.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_d.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_e.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_f.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_g.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_h.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_i.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_j.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_k.png +0 -0
- roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_l.png +0 -0
- roc_curves/Twins_SVT_ROC_a.png +0 -0
- roc_curves/Twins_SVT_ROC_b.png +0 -0
- roc_curves/Twins_SVT_ROC_c.png +0 -0
- roc_curves/Twins_SVT_ROC_d.png +0 -0
- roc_curves/Twins_SVT_ROC_e.png +0 -0
- roc_curves/Twins_SVT_ROC_f.png +0 -0
- roc_curves/Twins_SVT_ROC_g.png +0 -0
- roc_curves/Twins_SVT_ROC_h.png +0 -0
- roc_curves/Twins_SVT_ROC_i.png +0 -0
- roc_curves/Twins_SVT_ROC_j.png +0 -0
- roc_curves/Twins_SVT_ROC_k.png +0 -0
- roc_curves/Twins_SVT_ROC_l.png +0 -0
- training_curves/Twins_SVT_accuracy.png +0 -0
- training_curves/Twins_SVT_auc.png +0 -0
- training_curves/Twins_SVT_combined_metrics.png +3 -0
- training_curves/Twins_SVT_f1.png +0 -0
- training_curves/Twins_SVT_loss.png +0 -0
- training_curves/Twins_SVT_metrics.csv +101 -0
- training_metrics.csv +101 -0
- training_notebook_b1.ipynb +3 -0
.gitattributes
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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training_curves/Twins_SVT_combined_metrics.png filter=lfs diff=lfs merge=lfs -text
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training_notebook_b1.ipynb filter=lfs diff=lfs merge=lfs -text
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README.md
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| 1 |
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---
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license: apache-2.0
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tags:
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- vision-transformer
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- image-classification
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- pytorch
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- timm
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- twins_svt
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- gravitational-lensing
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- strong-lensing
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- astronomy
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- astrophysics
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datasets:
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- J24
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metrics:
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- accuracy
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- auc
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- f1
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model-index:
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- name: Twins_SVT-b1
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results:
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- task:
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type: image-classification
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name: Strong Gravitational Lens Discovery
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dataset:
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type: common-test-sample
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name: Common Test Sample (More et al. 2024)
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metrics:
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- type: accuracy
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value: 0.7208
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name: Average Accuracy
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- type: auc
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value: 0.6534
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name: Average AUC-ROC
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- type: f1
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value: 0.3320
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name: Average F1-Score
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---
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# 🌌 twins_svt-gravit-b1
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🔭 This model is part of **GraViT**: Transfer Learning with Vision Transformers and MLP-Mixer for Strong Gravitational Lens Discovery
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🔗 **GitHub Repository**: [https://github.com/parlange/gravit](https://github.com/parlange/gravit)
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## 🛰️ Model Details
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- **🤖 Model Type**: Twins_SVT
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- **🧪 Experiment**: B1 - J24-classification-head
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- **🌌 Dataset**: J24
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- **🪐 Fine-tuning Strategy**: classification-head
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## 💻 Quick Start
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```python
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import torch
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import timm
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# Load the model directly from the Hub
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model = timm.create_model(
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'hf-hub:parlange/twins_svt-gravit-b1',
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pretrained=True
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)
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model.eval()
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# Example inference
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dummy_input = torch.randn(1, 3, 224, 224)
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with torch.no_grad():
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output = model(dummy_input)
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predictions = torch.softmax(output, dim=1)
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print(f"Lens probability: {predictions[0][1]:.4f}")
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```
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## ⚡️ Training Configuration
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**Training Dataset:** J24 (Jaelani et al. 2024)
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**Fine-tuning Strategy:** classification-head
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| 82 |
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| 🔧 Parameter | 📝 Value |
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| 83 |
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|--------------|----------|
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| Batch Size | 192 |
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| Learning Rate | AdamW with ReduceLROnPlateau |
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| Epochs | 100 |
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| Patience | 10 |
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| 88 |
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| Optimizer | AdamW |
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| 89 |
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| Scheduler | ReduceLROnPlateau |
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| Image Size | 224x224 |
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| Fine Tune Mode | classification_head |
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| Stochastic Depth Probability | 0.1 |
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## 📈 Training Curves
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## 🏁 Final Epoch Training Metrics
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| Metric | Training | Validation |
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|:---------:|:-----------:|:-------------:|
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| 📉 Loss | 0.2461 | 0.2251 |
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| 🎯 Accuracy | 0.9027 | 0.9126 |
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| 📊 AUC-ROC | 0.9624 | 0.9686 |
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| ⚖️ F1 Score | 0.9013 | 0.9111 |
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## ☑️ Evaluation Results
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### ROC Curves and Confusion Matrices
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Performance across all test datasets (a through l) in the Common Test Sample (More et al. 2024):
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### 📋 Performance Summary
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Average performance across 12 test datasets from the Common Test Sample (More et al. 2024):
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| Metric | Value |
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|-----------|----------|
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| 🎯 Average Accuracy | 0.7208 |
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| 📈 Average AUC-ROC | 0.6534 |
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| 137 |
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| ⚖️ Average F1-Score | 0.3320 |
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| 138 |
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## 📘 Citation
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If you use this model in your research, please cite:
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| 143 |
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| 144 |
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```bibtex
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| 145 |
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@misc{parlange2025gravit,
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| 146 |
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title={GraViT: Transfer Learning with Vision Transformers and MLP-Mixer for Strong Gravitational Lens Discovery},
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author={René Parlange and Juan C. Cuevas-Tello and Octavio Valenzuela and Omar de J. Cabrera-Rosas and Tomás Verdugo and Anupreeta More and Anton T. Jaelani},
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| 148 |
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year={2025},
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| 149 |
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eprint={2509.00226},
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| 150 |
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archivePrefix={arXiv},
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| 151 |
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primaryClass={cs.CV},
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| 152 |
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url={https://arxiv.org/abs/2509.00226},
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}
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```
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---
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## Model Card Contact
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For questions about this model, please contact the author through: https://github.com/parlange/
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config.json
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{
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"architecture": "vit_base_patch16_224",
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| 3 |
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"num_classes": 2,
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| 4 |
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"num_features": 1000,
|
| 5 |
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"global_pool": "avg",
|
| 6 |
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"crop_pct": 0.875,
|
| 7 |
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"interpolation": "bicubic",
|
| 8 |
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"mean": [
|
| 9 |
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0.485,
|
| 10 |
+
0.456,
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| 11 |
+
0.406
|
| 12 |
+
],
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| 13 |
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"std": [
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| 14 |
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0.229,
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| 15 |
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0.224,
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| 16 |
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0.225
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| 17 |
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],
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| 18 |
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"first_conv": "conv1",
|
| 19 |
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"classifier": "fc",
|
| 20 |
+
"input_size": [
|
| 21 |
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3,
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| 22 |
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224,
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| 23 |
+
224
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| 24 |
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],
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| 25 |
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"pool_size": [
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| 26 |
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7,
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| 27 |
+
7
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| 28 |
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],
|
| 29 |
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"pretrained_cfg": {
|
| 30 |
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"tag": "gravit_b1",
|
| 31 |
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"custom_load": false,
|
| 32 |
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"input_size": [
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| 33 |
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3,
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| 34 |
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224,
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| 35 |
+
224
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| 36 |
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],
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| 37 |
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"fixed_input_size": true,
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| 38 |
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"interpolation": "bicubic",
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| 39 |
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"crop_pct": 0.875,
|
| 40 |
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"crop_mode": "center",
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| 41 |
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"mean": [
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| 42 |
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0.485,
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0.456,
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0.406
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],
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"std": [
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| 47 |
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0.229,
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0.224,
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| 49 |
+
0.225
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| 50 |
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],
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| 51 |
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"num_classes": 2,
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| 52 |
+
"pool_size": [
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| 53 |
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7,
|
| 54 |
+
7
|
| 55 |
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],
|
| 56 |
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"first_conv": "conv1",
|
| 57 |
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"classifier": "fc"
|
| 58 |
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},
|
| 59 |
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"model_name": "twins_svt_gravit_b1",
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| 60 |
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"experiment": "b1",
|
| 61 |
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"training_strategy": "classification-head",
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| 62 |
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"dataset": "J24",
|
| 63 |
+
"hyperparameters": {
|
| 64 |
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"batch_size": "192",
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| 65 |
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"learning_rate": "AdamW with ReduceLROnPlateau",
|
| 66 |
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"epochs": "100",
|
| 67 |
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"patience": "10",
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| 68 |
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"optimizer": "AdamW",
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| 69 |
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"scheduler": "ReduceLROnPlateau",
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| 70 |
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"image_size": "224x224",
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| 71 |
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"fine_tune_mode": "classification_head",
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| 72 |
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"stochastic_depth_probability": "0.1"
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| 73 |
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},
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| 74 |
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"hf_hub_id": "parlange/twins_svt-gravit-b1",
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| 75 |
+
"license": "apache-2.0"
|
| 76 |
+
}
|
confusion_matrices/Twins_SVT_Confusion_Matrix_a.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_b.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_c.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_d.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_e.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_f.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_g.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_h.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_i.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_j.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_k.png
ADDED
|
confusion_matrices/Twins_SVT_Confusion_Matrix_l.png
ADDED
|
evaluation_results.csv
ADDED
|
@@ -0,0 +1,133 @@
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|
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|
|
|
| 1 |
+
Model,Dataset,Loss,Accuracy,AUCROC,F1
|
| 2 |
+
ViT,a,0.6071771883394912,0.6972650110028293,0.630304788213628,0.16041848299912817
|
| 3 |
+
ViT,b,0.5153288846587805,0.7585664885256209,0.7058489871086556,0.19327731092436976
|
| 4 |
+
ViT,c,0.7054783390475984,0.6321911348632505,0.5800184162062615,0.1358936484490399
|
| 5 |
+
ViT,d,0.4042277384557577,0.8236403646651996,0.7250165745856354,0.24697986577181208
|
| 6 |
+
ViT,e,0.5327941425283707,0.7420417124039517,0.7240974797547869,0.43914081145584727
|
| 7 |
+
ViT,f,0.5265797158730187,0.7412284098830455,0.6639558097850381,0.05219858156028369
|
| 8 |
+
ViT,g,0.6893135578632354,0.6621666666666667,0.7476270555555556,0.6197711498780717
|
| 9 |
+
ViT,h,0.790124472618103,0.5951666666666666,0.625018,0.5763125763125763
|
| 10 |
+
ViT,i,0.6304114277362823,0.6966666666666667,0.7770440555555556,0.644808743169399
|
| 11 |
+
ViT,j,0.465672768831253,0.776,0.864817,0.7765214499501164
|
| 12 |
+
ViT,k,0.4067706377506256,0.8105,0.8964317777777777,0.8042018253831582
|
| 13 |
+
ViT,l,0.5734097661542007,0.7168843530220507,0.7773444022320638,0.6037596210775606
|
| 14 |
+
MLP-Mixer,a,0.46569699331935344,0.7956617415906948,0.6377578268876612,0.17091836734693877
|
| 15 |
+
MLP-Mixer,b,0.4452243679182891,0.8113800691606413,0.680889502762431,0.18256130790190736
|
| 16 |
+
MLP-Mixer,c,0.47408608185799006,0.7922037095253065,0.6053204419889502,0.16855345911949685
|
| 17 |
+
MLP-Mixer,d,0.42086313657886537,0.8296133291417793,0.628830570902394,0.19822485207100593
|
| 18 |
+
MLP-Mixer,e,0.5369727452879549,0.7694840834248079,0.669424052069931,0.38953488372093026
|
| 19 |
+
MLP-Mixer,f,0.4062789948943527,0.8290604910541399,0.6399901481253227,0.05724049551473729
|
| 20 |
+
MLP-Mixer,g,0.8928026676177978,0.5668333333333333,0.6760506666666667,0.4056711639606677
|
| 21 |
+
MLP-Mixer,h,0.9081041851043701,0.5566666666666666,0.5911980555555556,0.4000902119981958
|
| 22 |
+
MLP-Mixer,i,0.8798871593475341,0.5765,0.6166056111111111,0.4111239860950174
|
| 23 |
+
MLP-Mixer,j,0.46018748569488527,0.7815,0.874597,0.7684154742978272
|
| 24 |
+
MLP-Mixer,k,0.44727197551727294,0.7911666666666667,0.8744243888888887,0.7763698018918437
|
| 25 |
+
MLP-Mixer,l,0.5829932733619303,0.7279361218338534,0.7454255642147913,0.5488029465930019
|
| 26 |
+
CvT,a,0.7422070925208016,0.5998113800691607,0.3903342541436464,0.06876371616678859
|
| 27 |
+
CvT,b,0.5952609254949612,0.7066960075447972,0.4973591160220995,0.09152872444011685
|
| 28 |
+
CvT,c,0.723317504959712,0.6139578748821125,0.3812725598526704,0.07110438729198185
|
| 29 |
+
CvT,d,0.430008566209034,0.8365293932725558,0.5662173112338857,0.15309446254071662
|
| 30 |
+
CvT,e,0.6766743037101335,0.6871569703622393,0.5160750775751155,0.24802110817941952
|
| 31 |
+
CvT,f,0.5791996195594972,0.7131903028425374,0.4620804815700503,0.02475638662101659
|
| 32 |
+
CvT,g,1.034350182056427,0.45866666666666667,0.46588566666666664,0.25333333333333335
|
| 33 |
+
CvT,h,1.1022415161132812,0.4095,0.33246555555555557,0.23724434876210979
|
| 34 |
+
CvT,i,0.9467389023303986,0.5275,0.5413065,0.27990855981711965
|
| 35 |
+
CvT,j,0.6915355019569397,0.6251666666666666,0.6959060000000001,0.5795475789867265
|
| 36 |
+
CvT,k,0.6039242098331451,0.694,0.7733503333333334,0.6280388978930308
|
| 37 |
+
CvT,l,0.7708275838721139,0.5980117391994078,0.5461840780345415,0.3610690872415532
|
| 38 |
+
Swin,a,0.3745372065280601,0.8440741905061302,0.7235939226519337,0.2392638036809816
|
| 39 |
+
Swin,b,0.4118781376750692,0.8274127632819868,0.7413885819521178,0.22127659574468084
|
| 40 |
+
Swin,c,0.41712035007800596,0.8258409305249922,0.6833775322283611,0.21971830985915494
|
| 41 |
+
Swin,d,0.3414299682939776,0.867966048412449,0.7282725598526704,0.2708333333333333
|
| 42 |
+
Swin,e,0.47762388664856964,0.7881448957189902,0.7537349579959131,0.4469914040114613
|
| 43 |
+
Swin,f,0.34434392800953245,0.86058399814112,0.7211409512484105,0.07975460122699386
|
| 44 |
+
Swin,g,0.9412130119800568,0.562,0.687752,0.38367729831144465
|
| 45 |
+
Swin,h,0.9439922497272492,0.5611666666666667,0.600395,0.38322792223003044
|
| 46 |
+
Swin,i,0.9038637335300446,0.5835,0.6599881666666667,0.39564691656590084
|
| 47 |
+
Swin,j,0.41330916619300845,0.811,0.8991051666666667,0.8030566168808614
|
| 48 |
+
Swin,k,0.3759598867893219,0.8325,0.9137093333333334,0.8214602949014035
|
| 49 |
+
Swin,l,0.5501825281197098,0.7530537782243139,0.776428683903603,0.5787479704131336
|
| 50 |
+
CaiT,a,0.5068589627499177,0.7544797233574347,0.6288020257826887,0.1574973031283711
|
| 51 |
+
CaiT,b,0.43441846407422924,0.8022634391700723,0.7139318600368323,0.18838709677419355
|
| 52 |
+
CaiT,c,0.6128005658594627,0.675888085507702,0.5577274401473297,0.12404418011894647
|
| 53 |
+
CaiT,d,0.601496650358672,0.6966362779000315,0.5815893186003683,0.13141314131413143
|
| 54 |
+
CaiT,e,0.4804434718075489,0.7683863885839737,0.7282903201392568,0.40896358543417366
|
| 55 |
+
CaiT,f,0.4994646750235297,0.7533111300441484,0.6266931553341174,0.04383068147703392
|
| 56 |
+
CaiT,g,0.9582805759906768,0.5296666666666666,0.6336772222222222,0.33127962085308055
|
| 57 |
+
CaiT,h,1.052852813243866,0.46266666666666667,0.4407098888888889,0.30246646473388145
|
| 58 |
+
CaiT,i,1.0468598504066466,0.4736666666666667,0.4733858888888889,0.30684811237928006
|
| 59 |
+
CaiT,j,0.3563543026447296,0.8453333333333334,0.9224438888888887,0.8482172064115145
|
| 60 |
+
CaiT,k,0.44493358278274536,0.7893333333333333,0.8849772222222221,0.804031007751938
|
| 61 |
+
CaiT,l,0.634319533465761,0.6883824229284543,0.7108943442597637,0.5331537669333756
|
| 62 |
+
DeiT,a,0.4427877041630983,0.808236403646652,0.6191058931860037,0.18666666666666668
|
| 63 |
+
DeiT,b,0.41083011003044256,0.821754165356806,0.6952081031307551,0.19801980198019803
|
| 64 |
+
DeiT,c,0.4910275342516163,0.78528764539453,0.5721933701657459,0.1701093560145808
|
| 65 |
+
DeiT,d,0.5752349910365827,0.7318453316567117,0.5411786372007367,0.14098690835850958
|
| 66 |
+
DeiT,e,0.5283474334148622,0.8002195389681669,0.6915310678876864,0.43478260869565216
|
| 67 |
+
DeiT,f,0.42157146472453,0.8101618774688251,0.6117734242425559,0.05403319181783095
|
| 68 |
+
DeiT,g,1.163999383211136,0.5158333333333334,0.6234185555555556,0.2750187172448216
|
| 69 |
+
DeiT,h,1.206517367362976,0.4965,0.45666055555555557,0.2672811059907834
|
| 70 |
+
DeiT,i,1.2511613540649413,0.4681666666666667,0.42239144444444443,0.2566969485208479
|
| 71 |
+
DeiT,j,0.33839035058021544,0.8516666666666667,0.9297900555555554,0.8522085685818664
|
| 72 |
+
DeiT,k,0.425552321434021,0.804,0.8934688888888889,0.813570069752695
|
| 73 |
+
DeiT,l,0.6565662104555468,0.7179419385542806,0.7109608633913852,0.5444140758455757
|
| 74 |
+
DeiT3,a,0.4096169373367763,0.8371581263753537,0.5791758747697975,0.14802631578947367
|
| 75 |
+
DeiT3,b,0.373094875785923,0.8462747563659226,0.6644051565377532,0.15544041450777202
|
| 76 |
+
DeiT3,c,0.4991895148717394,0.77648538195536,0.5115930018416206,0.11235955056179775
|
| 77 |
+
DeiT3,d,0.38327455564663493,0.8513046211883055,0.6100073664825046,0.15985790408525755
|
| 78 |
+
DeiT3,e,0.5367149264438223,0.7815587266739846,0.6753273291455385,0.31141868512110726
|
| 79 |
+
DeiT3,f,0.3471956718102791,0.8570211447602819,0.5961145855485585,0.04648760330578512
|
| 80 |
+
DeiT3,g,1.3192027564048767,0.5021666666666667,0.5601109444444445,0.19682710406023124
|
| 81 |
+
DeiT3,h,1.3860539412498474,0.4651666666666667,0.3733101111111111,0.18573965998477543
|
| 82 |
+
DeiT3,i,1.324599706172943,0.5048333333333334,0.48481599999999997,0.19767755873615986
|
| 83 |
+
DeiT3,j,0.3928017973899841,0.8296666666666667,0.9115283333333334,0.8201970443349754
|
| 84 |
+
DeiT3,k,0.39819873094558716,0.8323333333333334,0.9044895555555555,0.8225123500352858
|
| 85 |
+
DeiT3,l,0.6891573654383029,0.7277246047274073,0.6817385665953223,0.5157528449167685
|
| 86 |
+
Twins_SVT,a,0.4458898261016137,0.8167243005344231,0.6354576427255985,0.2024623803009576
|
| 87 |
+
Twins_SVT,b,0.4509238941663468,0.8076076705438542,0.6965340699815838,0.19473684210526315
|
| 88 |
+
Twins_SVT,c,0.5059725925331032,0.7771141150581579,0.5930441988950277,0.17269544924154026
|
| 89 |
+
Twins_SVT,d,0.3316556203013057,0.8827412763281987,0.7198434622467773,0.2840690978886756
|
| 90 |
+
Twins_SVT,e,0.5185028320806087,0.7738748627881449,0.7086581397108906,0.4180790960451977
|
| 91 |
+
Twins_SVT,f,0.39142251728201677,0.8408333978777787,0.6639401856666073,0.06718111665910123
|
| 92 |
+
Twins_SVT,g,1.2193830106258392,0.4841666666666667,0.5380571111111111,0.20945083014048532
|
| 93 |
+
Twins_SVT,h,1.2485679879188538,0.468,0.36677261111111115,0.20438683948155534
|
| 94 |
+
Twins_SVT,i,1.1561509382724762,0.524,0.5393812222222223,0.22306855277475518
|
| 95 |
+
Twins_SVT,j,0.52089257979393,0.764,0.8455504444444444,0.7468716481944941
|
| 96 |
+
Twins_SVT,k,0.4576605150699615,0.8038333333333333,0.8778117222222223,0.7802054154995332
|
| 97 |
+
Twins_SVT,l,0.6924283070618104,0.7062027391465284,0.6558977267715866,0.48084470192487383
|
| 98 |
+
Twins_PCPVT,a,0.4554920045694665,0.7925180760767054,0.6320966850828729,0.1770573566084788
|
| 99 |
+
Twins_PCPVT,b,0.3702721736671714,0.8337000943099654,0.7290699815837937,0.21162444113263784
|
| 100 |
+
Twins_PCPVT,c,0.5222789617650578,0.7601383212826155,0.5801896869244936,0.1569060773480663
|
| 101 |
+
Twins_PCPVT,d,0.511706690917934,0.7695693178245835,0.6062357274401473,0.16228571428571428
|
| 102 |
+
Twins_PCPVT,e,0.44942784803366426,0.8111964873765093,0.764065692878226,0.45222929936305734
|
| 103 |
+
Twins_PCPVT,f,0.4167008115512896,0.8127952908372705,0.6441899979601845,0.05549042594763579
|
| 104 |
+
Twins_PCPVT,g,0.9797230496406555,0.5426666666666666,0.6615357222222222,0.32975085490962386
|
| 105 |
+
Twins_PCPVT,h,1.0603120126724244,0.5036666666666667,0.47164805555555556,0.31192236598890943
|
| 106 |
+
Twins_PCPVT,i,1.0547069294452667,0.5086666666666667,0.5087028888888889,0.3140995812005584
|
| 107 |
+
Twins_PCPVT,j,0.3549184784889221,0.845,0.9234385555555554,0.8425863236289777
|
| 108 |
+
Twins_PCPVT,k,0.42990235447883607,0.811,0.8866837222222221,0.8144633507853403
|
| 109 |
+
Twins_PCPVT,l,0.6083674293331931,0.7222251599598117,0.7249629563166041,0.5519065085728909
|
| 110 |
+
PiT,a,0.40825032295951375,0.8340144608613643,0.685341620626151,0.23919308357348704
|
| 111 |
+
PiT,b,0.4585393214237012,0.8057214712354606,0.7131197053406997,0.21173469387755103
|
| 112 |
+
PiT,c,0.46198257697112005,0.8072933039924552,0.636451197053407,0.21309370988446727
|
| 113 |
+
PiT,d,0.4301266003352072,0.8198679660484125,0.6617108655616942,0.22462787550744248
|
| 114 |
+
PiT,e,0.47335477670579,0.8111964873765093,0.7555210777264815,0.4911242603550296
|
| 115 |
+
PiT,f,0.38904998775843674,0.836418557818914,0.6788217244686715,0.07287093942054433
|
| 116 |
+
PiT,g,1.0988447036743163,0.5483333333333333,0.6416311666666666,0.3741339491916859
|
| 117 |
+
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model.safetensors
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roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_c.png
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roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_d.png
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roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_i.png
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roc_confusion_matrix/Twins_SVT_roc_confusion_matrix_l.png
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roc_curves/Twins_SVT_ROC_a.png
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training_curves/Twins_SVT_accuracy.png
ADDED
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training_curves/Twins_SVT_auc.png
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training_curves/Twins_SVT_combined_metrics.png
ADDED
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Git LFS Details
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training_curves/Twins_SVT_f1.png
ADDED
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training_curves/Twins_SVT_loss.png
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training_curves/Twins_SVT_metrics.csv
ADDED
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99,0.2464908709389281,0.22444128420000292,0.9031138940599086,0.912647374062165,0.9622997920209329,0.9686044280858229,0.9015843910265593,0.9106849315068493
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100,0.24613999790357724,0.22510776033930457,0.9026908106278558,0.912647374062165,0.962438579552298,0.9685561793428751,0.9012819045438938,0.9110747408619749
|
training_metrics.csv
ADDED
|
@@ -0,0 +1,101 @@
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| 1 |
+
epoch,train_loss,val_loss,train_accuracy,val_accuracy,train_auc,val_auc,train_f1,val_f1
|
| 2 |
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28,0.2747110759098329,0.25293756470419587,0.8918598747673041,0.9046087888531619,0.9543766464322665,0.9617697638913302,0.8899982785333104,0.9031556039173014
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|
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training_notebook_b1.ipynb
ADDED
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