Hugging Face's logo

hkivancoral
/
smids_5x_beit_base_rms_001_fold5

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
hkivancoral commited on
Commit
521b93d
•
1 Parent(s): bca3149

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: microsoft/beit-base-patch16-224
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - imagefolder
8
+ metrics:
9
+ - accuracy
10
+ model-index:
11
+ - name: smids_5x_beit_base_rms_001_fold5
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: 0.8216666666666667
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_5x_beit_base_rms_001_fold5
32
+
33
+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
34
+ It achieves the following results on the evaluation set:
35
+ - Loss: 1.3262
36
+ - Accuracy: 0.8217
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: 0.001
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
+ | 0.931 | 1.0 | 375 | 0.8668 | 0.5083 |
69
+ | 0.8597 | 2.0 | 750 | 0.7892 | 0.6017 |
70
+ | 0.7587 | 3.0 | 1125 | 0.7350 | 0.6383 |
71
+ | 0.7046 | 4.0 | 1500 | 0.7282 | 0.65 |
72
+ | 0.6817 | 5.0 | 1875 | 0.7027 | 0.6567 |
73
+ | 0.6292 | 6.0 | 2250 | 0.6987 | 0.6683 |
74
+ | 0.6024 | 7.0 | 2625 | 0.5984 | 0.7267 |
75
+ | 0.6528 | 8.0 | 3000 | 0.5956 | 0.7267 |
76
+ | 0.5546 | 9.0 | 3375 | 0.5629 | 0.765 |
77
+ | 0.4767 | 10.0 | 3750 | 0.5576 | 0.75 |
78
+ | 0.4967 | 11.0 | 4125 | 0.4703 | 0.8017 |
79
+ | 0.3904 | 12.0 | 4500 | 0.4630 | 0.8083 |
80
+ | 0.395 | 13.0 | 4875 | 0.4837 | 0.8 |
81
+ | 0.4102 | 14.0 | 5250 | 0.4887 | 0.815 |
82
+ | 0.4425 | 15.0 | 5625 | 0.4472 | 0.8317 |
83
+ | 0.269 | 16.0 | 6000 | 0.4817 | 0.8133 |
84
+ | 0.3554 | 17.0 | 6375 | 0.4030 | 0.8483 |
85
+ | 0.3667 | 18.0 | 6750 | 0.4187 | 0.83 |
86
+ | 0.2943 | 19.0 | 7125 | 0.4575 | 0.8333 |
87
+ | 0.2361 | 20.0 | 7500 | 0.4670 | 0.8317 |
88
+ | 0.2672 | 21.0 | 7875 | 0.4447 | 0.8383 |
89
+ | 0.2065 | 22.0 | 8250 | 0.4671 | 0.8267 |
90
+ | 0.3036 | 23.0 | 8625 | 0.5659 | 0.8167 |
91
+ | 0.1998 | 24.0 | 9000 | 0.5359 | 0.8233 |
92
+ | 0.1813 | 25.0 | 9375 | 0.4898 | 0.85 |
93
+ | 0.16 | 26.0 | 9750 | 0.5701 | 0.835 |
94
+ | 0.1617 | 27.0 | 10125 | 0.5423 | 0.8333 |
95
+ | 0.1338 | 28.0 | 10500 | 0.5644 | 0.8483 |
96
+ | 0.1411 | 29.0 | 10875 | 0.5853 | 0.8267 |
97
+ | 0.0859 | 30.0 | 11250 | 0.6605 | 0.8217 |
98
+ | 0.101 | 31.0 | 11625 | 0.7234 | 0.8317 |
99
+ | 0.0828 | 32.0 | 12000 | 0.6563 | 0.8367 |
100
+ | 0.1039 | 33.0 | 12375 | 0.7913 | 0.82 |
101
+ | 0.0772 | 34.0 | 12750 | 0.8613 | 0.82 |
102
+ | 0.0737 | 35.0 | 13125 | 0.7477 | 0.8283 |
103
+ | 0.0714 | 36.0 | 13500 | 0.9064 | 0.83 |
104
+ | 0.0337 | 37.0 | 13875 | 0.8383 | 0.8367 |
105
+ | 0.094 | 38.0 | 14250 | 0.9398 | 0.8233 |
106
+ | 0.0203 | 39.0 | 14625 | 0.9121 | 0.8267 |
107
+ | 0.0289 | 40.0 | 15000 | 1.0830 | 0.8283 |
108
+ | 0.0242 | 41.0 | 15375 | 1.1069 | 0.825 |
109
+ | 0.0154 | 42.0 | 15750 | 1.1781 | 0.8117 |
110
+ | 0.009 | 43.0 | 16125 | 1.1755 | 0.8167 |
111
+ | 0.0144 | 44.0 | 16500 | 1.1730 | 0.8233 |
112
+ | 0.0239 | 45.0 | 16875 | 1.4682 | 0.8083 |
113
+ | 0.0221 | 46.0 | 17250 | 1.3105 | 0.82 |
114
+ | 0.0362 | 47.0 | 17625 | 1.3368 | 0.8317 |
115
+ | 0.0008 | 48.0 | 18000 | 1.2965 | 0.8317 |
116
+ | 0.0038 | 49.0 | 18375 | 1.2931 | 0.8317 |
117
+ | 0.0178 | 50.0 | 18750 | 1.3262 | 0.8217 |
118
+
119
+
120
+ ### Framework versions
121
+
122
+ - Transformers 4.32.1
123
+ - Pytorch 2.1.0+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 sha256:740f493056b1971bec221a436b4fa6f512e067b7d16932bf9d3fdfd61afd1b3f
3
  size 343133766
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9048033ea68140c5d8be8533e90e202d57707653be143785c349bcd095a03433
3
  size 343133766