File size: 1,338 Bytes
c6a58d1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
---
language: en
license: mit
library_name: timm
tags:
- image-classification
- vgg16_bn
- svhn
datasets: svhn
metrics:
- accuracy
model-index:
- name: vgg16_bn_svhn
results:
- task:
type: image-classification
dataset:
name: SVHN
type: svhn
metrics:
- type: accuracy
value: 0.961240012292563
---
# Model Card for Model ID
This model is a small vgg16_bn trained on svhn.
- **Test Accuracy:** 0.961240012292563
- **License:** MIT
## How to Get Started with the Model
Use the code below to get started with the model.
```python
import detectors
import timm
model = timm.create_model("vgg16_bn_svhn", pretrained=True)
```
## Training Data
Training data is svhn.
## Training Hyperparameters
- **config**: `scripts/train_configs/svhn.json`
- **model**: `vgg16_bn_svhn`
- **dataset**: `svhn`
- **batch_size**: `128`
- **epochs**: `300`
- **validation_frequency**: `5`
- **seed**: `1`
- **criterion**: `CrossEntropyLoss`
- **criterion_kwargs**: `{}`
- **optimizer**: `SGD`
- **lr**: `0.01`
- **optimizer_kwargs**: `{'momentum': 0.9, 'weight_decay': 0.0005}`
- **scheduler**: `MultiStepLR`
- **scheduler_kwargs**: `{'gamma': 0.1, 'milestones': [75, 100, 150, 225]}`
- **debug**: `False`
## Testing Data
Testing data is svhn.
---
This model card was created by Eduardo Dadalto. |