File size: 4,811 Bytes
be2f943
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
915508b
be2f943
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_1x_deit_base_rms_001_fold3
  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: 0.4186046511627907
---

<!-- 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_1x_deit_base_rms_001_fold3

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: 1.5945
- Accuracy: 0.4186

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 5.1656          | 0.2326   |
| 5.6353        | 2.0   | 12   | 2.9961          | 0.2558   |
| 5.6353        | 3.0   | 18   | 1.8729          | 0.2558   |
| 2.0815        | 4.0   | 24   | 2.9243          | 0.2558   |
| 1.6692        | 5.0   | 30   | 1.6813          | 0.2558   |
| 1.6692        | 6.0   | 36   | 1.4288          | 0.2558   |
| 1.5305        | 7.0   | 42   | 1.5132          | 0.2326   |
| 1.5305        | 8.0   | 48   | 1.7063          | 0.2558   |
| 1.5248        | 9.0   | 54   | 1.4498          | 0.2558   |
| 1.47          | 10.0  | 60   | 1.4163          | 0.2558   |
| 1.47          | 11.0  | 66   | 1.5259          | 0.2558   |
| 1.4904        | 12.0  | 72   | 1.3986          | 0.2326   |
| 1.4904        | 13.0  | 78   | 1.4224          | 0.2558   |
| 1.455         | 14.0  | 84   | 1.4163          | 0.2558   |
| 1.5854        | 15.0  | 90   | 1.3942          | 0.2558   |
| 1.5854        | 16.0  | 96   | 1.4547          | 0.2326   |
| 1.4305        | 17.0  | 102  | 1.3943          | 0.2558   |
| 1.4305        | 18.0  | 108  | 1.4560          | 0.2558   |
| 1.3943        | 19.0  | 114  | 1.3964          | 0.3023   |
| 1.4034        | 20.0  | 120  | 1.3547          | 0.3721   |
| 1.4034        | 21.0  | 126  | 2.6056          | 0.2791   |
| 1.3234        | 22.0  | 132  | 1.4424          | 0.3721   |
| 1.3234        | 23.0  | 138  | 1.4761          | 0.2558   |
| 1.2686        | 24.0  | 144  | 1.4102          | 0.3488   |
| 1.2011        | 25.0  | 150  | 1.4342          | 0.2791   |
| 1.2011        | 26.0  | 156  | 1.3674          | 0.2791   |
| 1.1732        | 27.0  | 162  | 2.0106          | 0.3488   |
| 1.1732        | 28.0  | 168  | 1.4114          | 0.3488   |
| 1.1299        | 29.0  | 174  | 1.4639          | 0.3488   |
| 1.1039        | 30.0  | 180  | 1.3928          | 0.3256   |
| 1.1039        | 31.0  | 186  | 1.5567          | 0.2791   |
| 1.099         | 32.0  | 192  | 1.3821          | 0.3488   |
| 1.099         | 33.0  | 198  | 1.4133          | 0.3023   |
| 1.0136        | 34.0  | 204  | 1.5753          | 0.3721   |
| 1.0481        | 35.0  | 210  | 1.4640          | 0.3953   |
| 1.0481        | 36.0  | 216  | 1.4956          | 0.3023   |
| 0.9705        | 37.0  | 222  | 1.4443          | 0.3488   |
| 0.9705        | 38.0  | 228  | 1.4615          | 0.3256   |
| 0.8983        | 39.0  | 234  | 1.4941          | 0.4186   |
| 0.899         | 40.0  | 240  | 1.5259          | 0.3488   |
| 0.899         | 41.0  | 246  | 1.5855          | 0.4419   |
| 0.8181        | 42.0  | 252  | 1.5945          | 0.4186   |
| 0.8181        | 43.0  | 258  | 1.5945          | 0.4186   |
| 0.8111        | 44.0  | 264  | 1.5945          | 0.4186   |
| 0.8316        | 45.0  | 270  | 1.5945          | 0.4186   |
| 0.8316        | 46.0  | 276  | 1.5945          | 0.4186   |
| 0.807         | 47.0  | 282  | 1.5945          | 0.4186   |
| 0.807         | 48.0  | 288  | 1.5945          | 0.4186   |
| 0.8545        | 49.0  | 294  | 1.5945          | 0.4186   |
| 0.798         | 50.0  | 300  | 1.5945          | 0.4186   |


### Framework versions

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