File size: 1,350 Bytes
0c27122
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
- densenet121
- cifar100
datasets: cifar100
metrics:
- accuracy
model-index:
- name: densenet121_cifar100
  results:
  - task:
      type: image-classification
    dataset:
      name: CIFAR-100
      type: cifar100
    metrics:
    - type: accuracy
      value: 0.7619
---

# Model Card for Model ID

This model is a small densenet121 trained on cifar100.

- **Test Accuracy:** 0.7619
- **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("densenet121_cifar100", pretrained=True)
```

## Training Data

Training data is cifar100.

## Training Hyperparameters


- **config**: `scripts/train_configs/cifar100.json`

- **model**: `densenet121_cifar100`

- **dataset**: `cifar100`

- **batch_size**: `128`

- **epochs**: `300`

- **validation_frequency**: `5`

- **seed**: `1`

- **criterion**: `CrossEntropyLoss`

- **criterion_kwargs**: `{}`

- **optimizer**: `SGD`

- **lr**: `0.1`

- **optimizer_kwargs**: `{'momentum': 0.9, 'weight_decay': 0.0005}`

- **scheduler**: `CosineAnnealingLR`

- **scheduler_kwargs**: `{'T_max': 280}`

- **debug**: `False`


## Testing Data

Testing data is cifar100.

---

This model card was created by Eduardo Dadalto.