Hugging Face's logo

hkivancoral
/
smids_10x_deit_tiny_adamax_0001_fold4

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
hkivancoral commited on
Commit
987cee9
•
1 Parent(s): 15f92f8

End of training

Browse files
Files changed (2) hide show
  1. README.md +125 -0
  2. pytorch_model.bin +1 -1
README.md ADDED
@@ -0,0 +1,125 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: facebook/deit-tiny-patch16-224
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - imagefolder
8
+ metrics:
9
+ - accuracy
10
+ model-index:
11
+ - name: smids_10x_deit_tiny_adamax_0001_fold4
12
+ results:
13
+ - task:
14
+ name: Image Classification
15
+ type: image-classification
16
+ dataset:
17
+ name: imagefolder
18
+ type: imagefolder
19
+ config: default
20
+ split: test
21
+ args: default
22
+ metrics:
23
+ - name: Accuracy
24
+ type: accuracy
25
+ value: 0.8916666666666667
26
+ ---
27
+
28
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
29
+ should probably proofread and complete it, then remove this comment. -->
30
+
31
+ # smids_10x_deit_tiny_adamax_0001_fold4
32
+
33
+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
34
+ It achieves the following results on the evaluation set:
35
+ - Loss: 1.1802
36
+ - Accuracy: 0.8917
37
+
38
+ ## Model description
39
+
40
+ More information needed
41
+
42
+ ## Intended uses & limitations
43
+
44
+ More information needed
45
+
46
+ ## Training and evaluation data
47
+
48
+ More information needed
49
+
50
+ ## Training procedure
51
+
52
+ ### Training hyperparameters
53
+
54
+ The following hyperparameters were used during training:
55
+ - learning_rate: 0.0001
56
+ - train_batch_size: 32
57
+ - eval_batch_size: 32
58
+ - seed: 42
59
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
+ - lr_scheduler_type: linear
61
+ - lr_scheduler_warmup_ratio: 0.1
62
+ - num_epochs: 50
63
+
64
+ ### Training results
65
+
66
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
68
+ | 0.2287 | 1.0 | 750 | 0.3453 | 0.8783 |
69
+ | 0.1774 | 2.0 | 1500 | 0.3819 | 0.8783 |
70
+ | 0.1288 | 3.0 | 2250 | 0.5077 | 0.8617 |
71
+ | 0.0591 | 4.0 | 3000 | 0.5258 | 0.8767 |
72
+ | 0.013 | 5.0 | 3750 | 0.7962 | 0.87 |
73
+ | 0.0441 | 6.0 | 4500 | 0.7798 | 0.875 |
74
+ | 0.0022 | 7.0 | 5250 | 0.8865 | 0.8783 |
75
+ | 0.0168 | 8.0 | 6000 | 0.9982 | 0.8817 |
76
+ | 0.0002 | 9.0 | 6750 | 0.9825 | 0.8833 |
77
+ | 0.012 | 10.0 | 7500 | 0.9837 | 0.8883 |
78
+ | 0.0139 | 11.0 | 8250 | 1.0185 | 0.88 |
79
+ | 0.0283 | 12.0 | 9000 | 1.0469 | 0.8767 |
80
+ | 0.0013 | 13.0 | 9750 | 1.1375 | 0.885 |
81
+ | 0.0051 | 14.0 | 10500 | 1.1468 | 0.8817 |
82
+ | 0.0 | 15.0 | 11250 | 1.1486 | 0.875 |
83
+ | 0.0211 | 16.0 | 12000 | 1.0421 | 0.8867 |
84
+ | 0.0 | 17.0 | 12750 | 1.1215 | 0.8783 |
85
+ | 0.0 | 18.0 | 13500 | 1.1501 | 0.8917 |
86
+ | 0.0001 | 19.0 | 14250 | 1.2352 | 0.88 |
87
+ | 0.0002 | 20.0 | 15000 | 1.2860 | 0.8883 |
88
+ | 0.0 | 21.0 | 15750 | 1.1704 | 0.8833 |
89
+ | 0.0 | 22.0 | 16500 | 1.0833 | 0.8933 |
90
+ | 0.0 | 23.0 | 17250 | 1.1109 | 0.8933 |
91
+ | 0.0 | 24.0 | 18000 | 1.1424 | 0.8933 |
92
+ | 0.0 | 25.0 | 18750 | 1.0812 | 0.89 |
93
+ | 0.0 | 26.0 | 19500 | 1.1046 | 0.8917 |
94
+ | 0.0 | 27.0 | 20250 | 1.1453 | 0.8883 |
95
+ | 0.0 | 28.0 | 21000 | 1.1203 | 0.885 |
96
+ | 0.0 | 29.0 | 21750 | 1.1015 | 0.8933 |
97
+ | 0.0 | 30.0 | 22500 | 1.1212 | 0.8967 |
98
+ | 0.0 | 31.0 | 23250 | 1.1480 | 0.8883 |
99
+ | 0.0 | 32.0 | 24000 | 1.1454 | 0.8833 |
100
+ | 0.0 | 33.0 | 24750 | 1.1314 | 0.8867 |
101
+ | 0.0 | 34.0 | 25500 | 1.1208 | 0.885 |
102
+ | 0.0 | 35.0 | 26250 | 1.1448 | 0.8833 |
103
+ | 0.0 | 36.0 | 27000 | 1.1486 | 0.8833 |
104
+ | 0.0 | 37.0 | 27750 | 1.1572 | 0.885 |
105
+ | 0.0 | 38.0 | 28500 | 1.1406 | 0.8867 |
106
+ | 0.0 | 39.0 | 29250 | 1.1768 | 0.89 |
107
+ | 0.0 | 40.0 | 30000 | 1.1690 | 0.885 |
108
+ | 0.0 | 41.0 | 30750 | 1.1715 | 0.8883 |
109
+ | 0.0 | 42.0 | 31500 | 1.1720 | 0.89 |
110
+ | 0.0 | 43.0 | 32250 | 1.1654 | 0.8917 |
111
+ | 0.0 | 44.0 | 33000 | 1.1692 | 0.8917 |
112
+ | 0.0 | 45.0 | 33750 | 1.1750 | 0.8917 |
113
+ | 0.0 | 46.0 | 34500 | 1.1770 | 0.8917 |
114
+ | 0.0 | 47.0 | 35250 | 1.1783 | 0.8917 |
115
+ | 0.0 | 48.0 | 36000 | 1.1786 | 0.8917 |
116
+ | 0.0 | 49.0 | 36750 | 1.1796 | 0.8917 |
117
+ | 0.0 | 50.0 | 37500 | 1.1802 | 0.8917 |
118
+
119
+
120
+ ### Framework versions
121
+
122
+ - Transformers 4.32.1
123
+ - Pytorch 2.1.1+cu121
124
+ - Datasets 2.12.0
125
+ - Tokenizers 0.13.2
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d7db5b500cb1163e2094dd8f634419feed284759b46350f9a4a8f214fee5f8b2
3
  size 22167850
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e77783523e2dd0f0f058edbd8efc20e8ed49650e1584095d1ef982696ed003eb
3
  size 22167850