Hugging Face's logo

Augusto777
/
swinv2-tiny-patch4-window8-256-ve-UH

Image Classification
Transformers
TensorBoard
Safetensors
swinv2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
Augusto777 commited on
Commit
06f2234
•
1 Parent(s): d0a2b3f

Model save

Browse files
Files changed (3) hide show
  1. README.md +142 -0
  2. model.safetensors +1 -1
  3. runs/Jun16_14-59-28_DESKTOP-SKBE9FB/events.out.tfevents.1718571569.DESKTOP-SKBE9FB.10988.0 +2 -2
README.md ADDED
@@ -0,0 +1,142 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: microsoft/swinv2-tiny-patch4-window8-256
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ model-index:
9
+ - name: swinv2-tiny-patch4-window8-256-ve-UH
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # swinv2-tiny-patch4-window8-256-ve-UH
17
+
18
+ This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.7686
21
+ - Accuracy: 0.6538
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 4e-05
41
+ - train_batch_size: 32
42
+ - eval_batch_size: 32
43
+ - seed: 42
44
+ - gradient_accumulation_steps: 4
45
+ - total_train_batch_size: 128
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: linear
48
+ - lr_scheduler_warmup_ratio: 0.1
49
+ - num_epochs: 80
50
+
51
+ ### Training results
52
+
53
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
54
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
55
+ | No log | 1.0 | 2 | 1.6092 | 0.4038 |
56
+ | No log | 2.0 | 4 | 1.6075 | 0.4231 |
57
+ | No log | 3.0 | 6 | 1.6037 | 0.4038 |
58
+ | No log | 4.0 | 8 | 1.5960 | 0.4038 |
59
+ | 1.6041 | 5.0 | 10 | 1.5820 | 0.4038 |
60
+ | 1.6041 | 6.0 | 12 | 1.5578 | 0.4038 |
61
+ | 1.6041 | 7.0 | 14 | 1.5218 | 0.4038 |
62
+ | 1.6041 | 8.0 | 16 | 1.4849 | 0.4038 |
63
+ | 1.6041 | 9.0 | 18 | 1.4459 | 0.4038 |
64
+ | 1.4962 | 10.0 | 20 | 1.4109 | 0.4038 |
65
+ | 1.4962 | 11.0 | 22 | 1.3941 | 0.4038 |
66
+ | 1.4962 | 12.0 | 24 | 1.3865 | 0.4038 |
67
+ | 1.4962 | 13.0 | 26 | 1.3754 | 0.4038 |
68
+ | 1.4962 | 14.0 | 28 | 1.3655 | 0.4038 |
69
+ | 1.3392 | 15.0 | 30 | 1.3794 | 0.4038 |
70
+ | 1.3392 | 16.0 | 32 | 1.3800 | 0.4038 |
71
+ | 1.3392 | 17.0 | 34 | 1.3404 | 0.4038 |
72
+ | 1.3392 | 18.0 | 36 | 1.3337 | 0.4038 |
73
+ | 1.3392 | 19.0 | 38 | 1.3602 | 0.4038 |
74
+ | 1.2738 | 20.0 | 40 | 1.3384 | 0.4038 |
75
+ | 1.2738 | 21.0 | 42 | 1.3248 | 0.4038 |
76
+ | 1.2738 | 22.0 | 44 | 1.2693 | 0.4038 |
77
+ | 1.2738 | 23.0 | 46 | 1.2395 | 0.4038 |
78
+ | 1.2738 | 24.0 | 48 | 1.2427 | 0.4038 |
79
+ | 1.2283 | 25.0 | 50 | 1.2885 | 0.4038 |
80
+ | 1.2283 | 26.0 | 52 | 1.2916 | 0.4038 |
81
+ | 1.2283 | 27.0 | 54 | 1.2353 | 0.4038 |
82
+ | 1.2283 | 28.0 | 56 | 1.2032 | 0.4038 |
83
+ | 1.2283 | 29.0 | 58 | 1.2100 | 0.5577 |
84
+ | 1.1804 | 30.0 | 60 | 1.2110 | 0.6154 |
85
+ | 1.1804 | 31.0 | 62 | 1.1710 | 0.6346 |
86
+ | 1.1804 | 32.0 | 64 | 1.1323 | 0.6154 |
87
+ | 1.1804 | 33.0 | 66 | 1.1083 | 0.5962 |
88
+ | 1.1804 | 34.0 | 68 | 1.0935 | 0.5962 |
89
+ | 1.0925 | 35.0 | 70 | 1.0853 | 0.6346 |
90
+ | 1.0925 | 36.0 | 72 | 1.0622 | 0.6731 |
91
+ | 1.0925 | 37.0 | 74 | 1.0154 | 0.7115 |
92
+ | 1.0925 | 38.0 | 76 | 0.9901 | 0.7115 |
93
+ | 1.0925 | 39.0 | 78 | 0.9925 | 0.6923 |
94
+ | 0.9981 | 40.0 | 80 | 0.9865 | 0.6731 |
95
+ | 0.9981 | 41.0 | 82 | 0.9540 | 0.6731 |
96
+ | 0.9981 | 42.0 | 84 | 0.9316 | 0.7115 |
97
+ | 0.9981 | 43.0 | 86 | 0.9304 | 0.7115 |
98
+ | 0.9981 | 44.0 | 88 | 0.9246 | 0.6923 |
99
+ | 0.9102 | 45.0 | 90 | 0.8785 | 0.7115 |
100
+ | 0.9102 | 46.0 | 92 | 0.8422 | 0.7115 |
101
+ | 0.9102 | 47.0 | 94 | 0.8381 | 0.7115 |
102
+ | 0.9102 | 48.0 | 96 | 0.8359 | 0.7115 |
103
+ | 0.9102 | 49.0 | 98 | 0.8444 | 0.7115 |
104
+ | 0.8496 | 50.0 | 100 | 0.8287 | 0.6731 |
105
+ | 0.8496 | 51.0 | 102 | 0.7973 | 0.6923 |
106
+ | 0.8496 | 52.0 | 104 | 0.7799 | 0.6923 |
107
+ | 0.8496 | 53.0 | 106 | 0.7780 | 0.6923 |
108
+ | 0.8496 | 54.0 | 108 | 0.7820 | 0.7115 |
109
+ | 0.7808 | 55.0 | 110 | 0.7896 | 0.7115 |
110
+ | 0.7808 | 56.0 | 112 | 0.7737 | 0.6923 |
111
+ | 0.7808 | 57.0 | 114 | 0.7631 | 0.6731 |
112
+ | 0.7808 | 58.0 | 116 | 0.7635 | 0.6538 |
113
+ | 0.7808 | 59.0 | 118 | 0.7779 | 0.6538 |
114
+ | 0.757 | 60.0 | 120 | 0.7990 | 0.6731 |
115
+ | 0.757 | 61.0 | 122 | 0.8222 | 0.6538 |
116
+ | 0.757 | 62.0 | 124 | 0.8204 | 0.6538 |
117
+ | 0.757 | 63.0 | 126 | 0.7964 | 0.6731 |
118
+ | 0.757 | 64.0 | 128 | 0.7818 | 0.6538 |
119
+ | 0.6919 | 65.0 | 130 | 0.7796 | 0.6346 |
120
+ | 0.6919 | 66.0 | 132 | 0.7831 | 0.6346 |
121
+ | 0.6919 | 67.0 | 134 | 0.7867 | 0.6346 |
122
+ | 0.6919 | 68.0 | 136 | 0.7856 | 0.6346 |
123
+ | 0.6919 | 69.0 | 138 | 0.7793 | 0.6538 |
124
+ | 0.6722 | 70.0 | 140 | 0.7736 | 0.6538 |
125
+ | 0.6722 | 71.0 | 142 | 0.7682 | 0.6538 |
126
+ | 0.6722 | 72.0 | 144 | 0.7681 | 0.6538 |
127
+ | 0.6722 | 73.0 | 146 | 0.7672 | 0.6538 |
128
+ | 0.6722 | 74.0 | 148 | 0.7655 | 0.6538 |
129
+ | 0.6642 | 75.0 | 150 | 0.7645 | 0.6538 |
130
+ | 0.6642 | 76.0 | 152 | 0.7658 | 0.6538 |
131
+ | 0.6642 | 77.0 | 154 | 0.7677 | 0.6538 |
132
+ | 0.6642 | 78.0 | 156 | 0.7683 | 0.6538 |
133
+ | 0.6642 | 79.0 | 158 | 0.7684 | 0.6538 |
134
+ | 0.6491 | 80.0 | 160 | 0.7686 | 0.6538 |
135
+
136
+
137
+ ### Framework versions
138
+
139
+ - Transformers 4.36.2
140
+ - Pytorch 2.1.2+cu118
141
+ - Datasets 2.16.1
142
+ - Tokenizers 0.15.0
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:0db1db8042fad2fe2caff2ca4a83f9b6ef437b842dc97aa26df56893e353a34b
3
  size 110359372
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f93b9fccca32cd1480235ab4191a39a0ebde58fb66f13aa2fa875e39c6fcf067
3
  size 110359372
runs/Jun16_14-59-28_DESKTOP-SKBE9FB/events.out.tfevents.1718571569.DESKTOP-SKBE9FB.10988.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:815be76122edaae9bbe9223c3a32d620b90d2115cc859f1084d871fa0ee8b8b6
3
- size 31983
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1da5151c2e6b4158e05e4265152f54dd728c257e9a6eb4edaca9424c8b4854b8
3
+ size 33140