Hugging Face's logo

Augusto777
/
swinv2-tiny-patch4-window8-256-ve-U13-b-80c

Image Classification
Transformers
TensorBoard
Safetensors
swinv2
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
Augusto777 commited on
Commit
86f5437
•
1 Parent(s): 36b41fb

Model save

Browse files
Files changed (3) hide show
  1. README.md +151 -0
  2. model.safetensors +1 -1
  3. runs/Jun12_11-31-48_DESKTOP-SKBE9FB/events.out.tfevents.1718213509.DESKTOP-SKBE9FB.10440.0 +2 -2
README.md ADDED
@@ -0,0 +1,151 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: microsoft/swinv2-tiny-patch4-window8-256
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - imagefolder
8
+ metrics:
9
+ - accuracy
10
+ model-index:
11
+ - name: swinv2-tiny-patch4-window8-256-ve-U13-b-80c
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: validation
21
+ args: default
22
+ metrics:
23
+ - name: Accuracy
24
+ type: accuracy
25
+ value: 0.6956521739130435
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
+ # swinv2-tiny-patch4-window8-256-ve-U13-b-80c
32
+
33
+ This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
34
+ It achieves the following results on the evaluation set:
35
+ - Loss: 1.1780
36
+ - Accuracy: 0.6957
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: 4e-05
56
+ - train_batch_size: 32
57
+ - eval_batch_size: 32
58
+ - seed: 42
59
+ - gradient_accumulation_steps: 4
60
+ - total_train_batch_size: 128
61
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
62
+ - lr_scheduler_type: linear
63
+ - lr_scheduler_warmup_ratio: 0.1
64
+ - num_epochs: 80
65
+
66
+ ### Training results
67
+
68
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
69
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
70
+ | No log | 0.92 | 6 | 1.6333 | 0.1087 |
71
+ | 1.4981 | 2.0 | 13 | 1.6225 | 0.1087 |
72
+ | 1.4981 | 2.92 | 19 | 1.5921 | 0.1087 |
73
+ | 1.4704 | 4.0 | 26 | 1.5001 | 0.1087 |
74
+ | 1.4116 | 4.92 | 32 | 1.4078 | 0.1087 |
75
+ | 1.4116 | 6.0 | 39 | 1.2960 | 0.3478 |
76
+ | 1.3094 | 6.92 | 45 | 1.2926 | 0.3043 |
77
+ | 1.2014 | 8.0 | 52 | 1.1532 | 0.5435 |
78
+ | 1.2014 | 8.92 | 58 | 1.1059 | 0.4783 |
79
+ | 1.0577 | 10.0 | 65 | 0.9510 | 0.6304 |
80
+ | 0.9185 | 10.92 | 71 | 0.9695 | 0.4783 |
81
+ | 0.9185 | 12.0 | 78 | 0.8792 | 0.6087 |
82
+ | 0.8369 | 12.92 | 84 | 0.8616 | 0.6957 |
83
+ | 0.7406 | 14.0 | 91 | 0.7816 | 0.6957 |
84
+ | 0.7406 | 14.92 | 97 | 0.7638 | 0.7609 |
85
+ | 0.6929 | 16.0 | 104 | 0.7710 | 0.7826 |
86
+ | 0.6192 | 16.92 | 110 | 0.7471 | 0.6957 |
87
+ | 0.6192 | 18.0 | 117 | 0.7265 | 0.7391 |
88
+ | 0.5936 | 18.92 | 123 | 0.7841 | 0.7609 |
89
+ | 0.5125 | 20.0 | 130 | 0.9320 | 0.6739 |
90
+ | 0.5125 | 20.92 | 136 | 0.7512 | 0.7609 |
91
+ | 0.4905 | 22.0 | 143 | 0.7466 | 0.6957 |
92
+ | 0.4905 | 22.92 | 149 | 0.8030 | 0.6957 |
93
+ | 0.4315 | 24.0 | 156 | 0.8184 | 0.7391 |
94
+ | 0.4272 | 24.92 | 162 | 0.8196 | 0.6957 |
95
+ | 0.4272 | 26.0 | 169 | 0.8712 | 0.6957 |
96
+ | 0.4261 | 26.92 | 175 | 0.7834 | 0.6957 |
97
+ | 0.4217 | 28.0 | 182 | 0.8394 | 0.6739 |
98
+ | 0.4217 | 28.92 | 188 | 0.9941 | 0.6739 |
99
+ | 0.3502 | 30.0 | 195 | 0.8909 | 0.7174 |
100
+ | 0.368 | 30.92 | 201 | 0.9995 | 0.7174 |
101
+ | 0.368 | 32.0 | 208 | 0.9418 | 0.6739 |
102
+ | 0.3473 | 32.92 | 214 | 0.8595 | 0.6739 |
103
+ | 0.3079 | 34.0 | 221 | 0.9562 | 0.6957 |
104
+ | 0.3079 | 34.92 | 227 | 0.8992 | 0.6739 |
105
+ | 0.3226 | 36.0 | 234 | 0.9908 | 0.6739 |
106
+ | 0.2603 | 36.92 | 240 | 0.9469 | 0.6957 |
107
+ | 0.2603 | 38.0 | 247 | 0.9942 | 0.6739 |
108
+ | 0.3028 | 38.92 | 253 | 1.0084 | 0.6739 |
109
+ | 0.2576 | 40.0 | 260 | 0.9908 | 0.6957 |
110
+ | 0.2576 | 40.92 | 266 | 1.0661 | 0.6957 |
111
+ | 0.2713 | 42.0 | 273 | 1.1347 | 0.6522 |
112
+ | 0.2713 | 42.92 | 279 | 1.1054 | 0.6739 |
113
+ | 0.2578 | 44.0 | 286 | 1.1089 | 0.6957 |
114
+ | 0.2367 | 44.92 | 292 | 1.1452 | 0.6739 |
115
+ | 0.2367 | 46.0 | 299 | 1.0272 | 0.6957 |
116
+ | 0.2301 | 46.92 | 305 | 1.1043 | 0.6739 |
117
+ | 0.2191 | 48.0 | 312 | 1.0815 | 0.6739 |
118
+ | 0.2191 | 48.92 | 318 | 0.9934 | 0.6957 |
119
+ | 0.2635 | 50.0 | 325 | 1.0866 | 0.6957 |
120
+ | 0.1874 | 50.92 | 331 | 1.0507 | 0.7174 |
121
+ | 0.1874 | 52.0 | 338 | 1.1002 | 0.7174 |
122
+ | 0.2057 | 52.92 | 344 | 1.0400 | 0.6739 |
123
+ | 0.1808 | 54.0 | 351 | 1.1092 | 0.7174 |
124
+ | 0.1808 | 54.92 | 357 | 1.1550 | 0.7174 |
125
+ | 0.2107 | 56.0 | 364 | 1.0579 | 0.6957 |
126
+ | 0.2149 | 56.92 | 370 | 1.0936 | 0.6957 |
127
+ | 0.2149 | 58.0 | 377 | 1.1692 | 0.6957 |
128
+ | 0.1865 | 58.92 | 383 | 1.1357 | 0.7174 |
129
+ | 0.1832 | 60.0 | 390 | 1.1549 | 0.6739 |
130
+ | 0.1832 | 60.92 | 396 | 1.1631 | 0.6957 |
131
+ | 0.1732 | 62.0 | 403 | 1.1312 | 0.6957 |
132
+ | 0.1732 | 62.92 | 409 | 1.1210 | 0.6957 |
133
+ | 0.1856 | 64.0 | 416 | 1.1835 | 0.6739 |
134
+ | 0.1503 | 64.92 | 422 | 1.1892 | 0.7174 |
135
+ | 0.1503 | 66.0 | 429 | 1.1865 | 0.6739 |
136
+ | 0.1713 | 66.92 | 435 | 1.1608 | 0.6739 |
137
+ | 0.1804 | 68.0 | 442 | 1.1699 | 0.6739 |
138
+ | 0.1804 | 68.92 | 448 | 1.1694 | 0.7174 |
139
+ | 0.1761 | 70.0 | 455 | 1.1744 | 0.6957 |
140
+ | 0.1619 | 70.92 | 461 | 1.1783 | 0.6957 |
141
+ | 0.1619 | 72.0 | 468 | 1.1797 | 0.6957 |
142
+ | 0.1649 | 72.92 | 474 | 1.1788 | 0.6957 |
143
+ | 0.1843 | 73.85 | 480 | 1.1780 | 0.6957 |
144
+
145
+
146
+ ### Framework versions
147
+
148
+ - Transformers 4.36.2
149
+ - Pytorch 2.1.2+cu118
150
+ - Datasets 2.16.1
151
+ - Tokenizers 0.15.0
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:27614f8e22d1d3d43881b97f8f4e3b4ec724042816eb4e33acbdec808858c438
3
  size 110356296
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c12023d4ac5d42030c2c7eea18ed9fd4b233919ad6d057f657713f7915ef5958
3
  size 110356296
runs/Jun12_11-31-48_DESKTOP-SKBE9FB/events.out.tfevents.1718213509.DESKTOP-SKBE9FB.10440.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8d63c007619a867e6ee032238fdad67688428c31fd422dacde7cb7d43d787d38
3
- size 34820
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:776d29980c5a02b29bd8da1d1e8ac0525b3c599675d586db1506e07a62a849c1
3
+ size 36457