Hugging Face's logo

Augusto777
/
swinv2-tiny-patch4-window8-256-DMAE-8e-6

TensorBoard
Safetensors
swinv2
Generated from Trainer
Eval Results
Model card Files Metrics Community
Augusto777 commited on
Commit
04aaa0f
·
verified ·
1 Parent(s): 741b91e

Model save

Browse files
Files changed (3) hide show
  1. README.md +112 -0
  2. model.safetensors +1 -1
  3. runs/Dec02_21-16-32_DESKTOP-SKBE9FB/events.out.tfevents.1733195793.DESKTOP-SKBE9FB.16940.0 +2 -2
README.md ADDED
@@ -0,0 +1,112 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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-DMAE-8e-6
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: 0.10869565217391304
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-DMAE-8e-6
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: 6.3664
36
+ - Accuracy: 0.1087
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: 8e-06
56
+ - train_batch_size: 16
57
+ - eval_batch_size: 16
58
+ - seed: 42
59
+ - gradient_accumulation_steps: 4
60
+ - total_train_batch_size: 64
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: 40
65
+
66
+ ### Training results
67
+
68
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
69
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
70
+ | No log | 0.86 | 3 | 7.9427 | 0.1087 |
71
+ | No log | 2.0 | 7 | 7.9381 | 0.1087 |
72
+ | 7.9636 | 2.86 | 10 | 7.9301 | 0.1087 |
73
+ | 7.9636 | 4.0 | 14 | 7.9088 | 0.1087 |
74
+ | 7.9636 | 4.86 | 17 | 7.8857 | 0.1087 |
75
+ | 7.8732 | 6.0 | 21 | 7.8450 | 0.1087 |
76
+ | 7.8732 | 6.86 | 24 | 7.8049 | 0.1087 |
77
+ | 7.8732 | 8.0 | 28 | 7.7376 | 0.1087 |
78
+ | 7.6568 | 8.86 | 31 | 7.6783 | 0.1087 |
79
+ | 7.6568 | 10.0 | 35 | 7.5943 | 0.1087 |
80
+ | 7.6568 | 10.86 | 38 | 7.5288 | 0.1087 |
81
+ | 7.7458 | 12.0 | 42 | 7.4353 | 0.1087 |
82
+ | 7.7458 | 12.86 | 45 | 7.3610 | 0.1087 |
83
+ | 7.7458 | 14.0 | 49 | 7.2614 | 0.1087 |
84
+ | 7.3025 | 14.86 | 52 | 7.1894 | 0.1087 |
85
+ | 7.3025 | 16.0 | 56 | 7.0993 | 0.1087 |
86
+ | 7.3025 | 16.86 | 59 | 7.0348 | 0.1087 |
87
+ | 7.0862 | 18.0 | 63 | 6.9525 | 0.1087 |
88
+ | 7.0862 | 18.86 | 66 | 6.8945 | 0.1087 |
89
+ | 6.9553 | 20.0 | 70 | 6.8253 | 0.1087 |
90
+ | 6.9553 | 20.86 | 73 | 6.7795 | 0.1087 |
91
+ | 6.9553 | 22.0 | 77 | 6.7202 | 0.1087 |
92
+ | 6.8024 | 22.86 | 80 | 6.6757 | 0.1087 |
93
+ | 6.8024 | 24.0 | 84 | 6.6210 | 0.1087 |
94
+ | 6.8024 | 24.86 | 87 | 6.5785 | 0.1087 |
95
+ | 6.6652 | 26.0 | 91 | 6.5275 | 0.1087 |
96
+ | 6.6652 | 26.86 | 94 | 6.4949 | 0.1087 |
97
+ | 6.6652 | 28.0 | 98 | 6.4589 | 0.1087 |
98
+ | 6.467 | 28.86 | 101 | 6.4354 | 0.1087 |
99
+ | 6.467 | 30.0 | 105 | 6.4094 | 0.1087 |
100
+ | 6.467 | 30.86 | 108 | 6.3946 | 0.1087 |
101
+ | 6.4984 | 32.0 | 112 | 6.3796 | 0.1087 |
102
+ | 6.4984 | 32.86 | 115 | 6.3719 | 0.1087 |
103
+ | 6.4984 | 34.0 | 119 | 6.3668 | 0.1087 |
104
+ | 6.4603 | 34.29 | 120 | 6.3664 | 0.1087 |
105
+
106
+
107
+ ### Framework versions
108
+
109
+ - Transformers 4.36.2
110
+ - Pytorch 2.1.2+cu118
111
+ - Datasets 2.16.1
112
+ - Tokenizers 0.15.0
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ab5853d9f4eaaacbf7ed33971b4bf862e6021f58bec628cdacad3b81f548a968
3
  size 110356296
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6c19c1cb61ed9f24e22ef053ed97cf6b58ee63f1991243208b0a67f4f27d3d9b
3
  size 110356296
runs/Dec02_21-16-32_DESKTOP-SKBE9FB/events.out.tfevents.1733195793.DESKTOP-SKBE9FB.16940.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:73aea9a9d6536968fd260673e78e872aa32b493df75af5a525c8789ab10ab026
3
- size 17278
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cc548699c55cde0185a92119274c346310f9ef53191e844a33dee43edd934786
3
+ size 18097