File size: 4,814 Bytes
0fe9114
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_base_rms_0001_fold2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5333333333333333
---

<!-- 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. -->

# hushem_5x_deit_base_rms_0001_fold2

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 5.1764
- Accuracy: 0.5333

## 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: 0.0001
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4732        | 1.0   | 27   | 1.5871          | 0.2667   |
| 1.4137        | 2.0   | 54   | 1.4271          | 0.2667   |
| 1.462         | 3.0   | 81   | 1.4098          | 0.2667   |
| 1.4423        | 4.0   | 108  | 1.4316          | 0.2444   |
| 1.4677        | 5.0   | 135  | 1.1736          | 0.6      |
| 1.1753        | 6.0   | 162  | 1.3090          | 0.4889   |
| 1.0628        | 7.0   | 189  | 1.1008          | 0.4      |
| 0.8856        | 8.0   | 216  | 1.3194          | 0.4667   |
| 0.7266        | 9.0   | 243  | 1.5517          | 0.4667   |
| 0.7206        | 10.0  | 270  | 1.5964          | 0.4222   |
| 0.6825        | 11.0  | 297  | 1.9511          | 0.5333   |
| 0.6024        | 12.0  | 324  | 1.1289          | 0.5111   |
| 0.7093        | 13.0  | 351  | 1.6051          | 0.4667   |
| 0.5446        | 14.0  | 378  | 1.0604          | 0.5333   |
| 0.4716        | 15.0  | 405  | 2.6293          | 0.5778   |
| 0.4728        | 16.0  | 432  | 3.2908          | 0.4889   |
| 0.5099        | 17.0  | 459  | 2.0246          | 0.5333   |
| 0.4809        | 18.0  | 486  | 3.4545          | 0.5333   |
| 0.3484        | 19.0  | 513  | 2.2451          | 0.5111   |
| 0.352         | 20.0  | 540  | 2.8572          | 0.4889   |
| 0.3258        | 21.0  | 567  | 3.5970          | 0.5556   |
| 0.2785        | 22.0  | 594  | 3.6404          | 0.5556   |
| 0.3005        | 23.0  | 621  | 3.6333          | 0.5111   |
| 0.2089        | 24.0  | 648  | 4.2561          | 0.5333   |
| 0.1996        | 25.0  | 675  | 3.8526          | 0.5111   |
| 0.1044        | 26.0  | 702  | 4.1245          | 0.5333   |
| 0.2042        | 27.0  | 729  | 3.9154          | 0.5556   |
| 0.1371        | 28.0  | 756  | 3.3906          | 0.5556   |
| 0.1014        | 29.0  | 783  | 4.2534          | 0.5556   |
| 0.0761        | 30.0  | 810  | 3.8328          | 0.5778   |
| 0.0321        | 31.0  | 837  | 4.5117          | 0.5556   |
| 0.1194        | 32.0  | 864  | 4.5296          | 0.5333   |
| 0.0072        | 33.0  | 891  | 4.9299          | 0.5333   |
| 0.0276        | 34.0  | 918  | 5.0433          | 0.5111   |
| 0.0121        | 35.0  | 945  | 4.9519          | 0.5333   |
| 0.0051        | 36.0  | 972  | 4.9546          | 0.5333   |
| 0.0001        | 37.0  | 999  | 4.9700          | 0.5111   |
| 0.0001        | 38.0  | 1026 | 4.9962          | 0.5111   |
| 0.0           | 39.0  | 1053 | 5.0319          | 0.5111   |
| 0.0           | 40.0  | 1080 | 5.0566          | 0.5111   |
| 0.0001        | 41.0  | 1107 | 5.0812          | 0.5333   |
| 0.0           | 42.0  | 1134 | 5.1051          | 0.5333   |
| 0.0           | 43.0  | 1161 | 5.1228          | 0.5333   |
| 0.0           | 44.0  | 1188 | 5.1393          | 0.5333   |
| 0.0           | 45.0  | 1215 | 5.1531          | 0.5333   |
| 0.0           | 46.0  | 1242 | 5.1647          | 0.5333   |
| 0.0           | 47.0  | 1269 | 5.1724          | 0.5333   |
| 0.0           | 48.0  | 1296 | 5.1763          | 0.5333   |
| 0.0           | 49.0  | 1323 | 5.1764          | 0.5333   |
| 0.0           | 50.0  | 1350 | 5.1764          | 0.5333   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0