Brief summary about the training configurations used:
Transfer Learning | Freeze Layers | Balance Classes | Segmentation | Data Augmentation | Normalization | Custom Optimizer | Callback | ConvNeXt | ResNetV2 | Xception |
---|---|---|---|---|---|---|---|---|---|---|
❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | Notebook | Notebook | Notebook |
❌ | ❌ | ✔️ | ❌ | ❌ | ❌ | ❌ | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ✔️ | ❌ | ❌ | StandardScaler | ❌ | ❌ | Notebook | Notebook | Notebook** |
✔️ | ✔️ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | Notebook | Notebook | Notebook |
❌ | ❌ | ❌ | ✔️ | ❌ | ❌ | ❌ | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ❌ | ✔️ | ❌ | Notebook** | Notebook** | Notebook** |
❌ | ❌ | ❌ | ❌ | ✔️ | ❌ | ❌ | ❌ | Notebook** | Notebook** | Notebook** |
✔️ | ✔️ | ❌ | ❌ | ✔️ | ❌ | ❌ | ❌ | Notebook** | Notebook** | Notebook** |
✔️ | ✔️ | ✔️ | ❌ | ✔️ | ❌ | ❌ | ❌ | Notebook** | Notebook** | Notebook** |
✔️ | ✔️ | ✔️ | ❌ | ✔️ | MinMaxScaler | ✔️ | ❌ | Notebook** | Notebook** | Not trained due to low RAM** |
✔️ | ✔️ | ❌ | ❌ | ✔️ | ❌ | ✔️ | ❌ | Notebook** | Notebook** | Notebook** |
✔️ | ✔️ | ✔️ | ❌ | ❌ | ❌ | ❌ | ❌ | Notebook** | Notebook** | Notebook** |
✔️ | ✔️ | ✔️ | ❌ | ❌ | ❌ | ✔️ | ❌ | Notebook** | Notebook** | Notebook** |
✔️ | ✔️ | ✔️ | ✔️ | ❌ | ❌ | ✔️ | ❌ | Notebook** | Notebook** | Notebook** |
Obs: Execution in Google Colaboratory with High-RAM (25.5 GB) and T4 as GPU.
** Execution in Google Colaboratory with High-RAM (83.5 GB) and A100 as GPU.
Vision Transformer Training
Model ViT_B/32 and TPU. Batch size was equal for all runs: 8 for each TPU core (64). Worth to notice that classes are unbalanced as well as the others parameters weren't calculated.
Epochs | Image Resolution | Accuracy without fine-tuning | Accuracy with fine-tuning | Notebook |
---|---|---|---|---|
100 | 224 | 0.02929688 | 0.7998047 | Notebook |
10 | 224 | 0.03125 | 0.7265625 | Notebook |
10 | 256 | 0.02539062 | 0.7158203 | Notebook |
Obs: Execution in Google Colaboratory with Standard RAM (12.7 GB) and TPU.
Brief summary about training configurations:
Transfer Learning | Freeze Layers | Balance Classes | Segmentation | Data Augmentation | GAN model | Normalization | Custom Optimizer | ConvNeXt | ResNetV2 | Xception |
---|---|---|---|---|---|---|---|---|---|---|
✔️ | ✔️ | ❌ | ❌ | ✔️ | 4 | ❌ | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ❌ | ❌ | ✔️ | 4 | StandardScaler | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ❌ | ❌ | ✔️ | 4 | MinMaxScaler | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ❌ | ❌ | ✔️ | 3 | ❌ | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ❌ | ❌ | ✔️ | 3 | StandardScaler | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ❌ | ❌ | ✔️ | 3 | MinMaxScaler | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ❌ | ✔️ | ✔️ | 3 | MinMaxScaler | ❌ | Notebook | Notebook | Notebook |
✔️ | ✔️ | ❌ | ✔️ | ✔️ | 3 | ❌ | ❌ | Notebook | Notebook | Notebook |
Execution in Google Colaboratory with High-RAM (83.5 GB) and A100 as GPU.