Hugging Face's logo

hkivancoral
/
hushem_5x_beit_base_sgd_0001_fold1

Image Classification
Transformers
TensorBoard
Safetensors
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
hkivancoral commited on
Commit
3806c31
•
1 Parent(s): cba8ea7

End of training

Browse files
Files changed (2) hide show
  1. README.md +53 -53
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.24444444444444444
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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: 1.5157
36
- - Accuracy: 0.2444
37
 
38
  ## Model description
39
 
@@ -65,56 +65,56 @@ The following hyperparameters were used during training:
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
- | 1.4822 | 1.0 | 27 | 1.6002 | 0.2667 |
69
- | 1.5214 | 2.0 | 54 | 1.5936 | 0.2667 |
70
- | 1.5576 | 3.0 | 81 | 1.5870 | 0.2667 |
71
- | 1.5472 | 4.0 | 108 | 1.5816 | 0.2667 |
72
- | 1.4716 | 5.0 | 135 | 1.5767 | 0.2667 |
73
- | 1.4758 | 6.0 | 162 | 1.5710 | 0.2667 |
74
- | 1.4611 | 7.0 | 189 | 1.5663 | 0.2667 |
75
- | 1.4821 | 8.0 | 216 | 1.5623 | 0.2667 |
76
- | 1.4618 | 9.0 | 243 | 1.5580 | 0.2667 |
77
- | 1.4567 | 10.0 | 270 | 1.5546 | 0.2667 |
78
- | 1.4567 | 11.0 | 297 | 1.5511 | 0.2667 |
79
- | 1.453 | 12.0 | 324 | 1.5484 | 0.2667 |
80
- | 1.3888 | 13.0 | 351 | 1.5457 | 0.2667 |
81
- | 1.4317 | 14.0 | 378 | 1.5428 | 0.2667 |
82
- | 1.3877 | 15.0 | 405 | 1.5404 | 0.2667 |
83
- | 1.4231 | 16.0 | 432 | 1.5382 | 0.2667 |
84
- | 1.3948 | 17.0 | 459 | 1.5365 | 0.2667 |
85
- | 1.4184 | 18.0 | 486 | 1.5346 | 0.2667 |
86
- | 1.4164 | 19.0 | 513 | 1.5325 | 0.2667 |
87
- | 1.4155 | 20.0 | 540 | 1.5309 | 0.2667 |
88
- | 1.4058 | 21.0 | 567 | 1.5293 | 0.2667 |
89
- | 1.3567 | 22.0 | 594 | 1.5276 | 0.2444 |
90
- | 1.3445 | 23.0 | 621 | 1.5270 | 0.2444 |
91
- | 1.3726 | 24.0 | 648 | 1.5258 | 0.2444 |
92
- | 1.3733 | 25.0 | 675 | 1.5248 | 0.2444 |
93
- | 1.386 | 26.0 | 702 | 1.5239 | 0.2444 |
94
- | 1.392 | 27.0 | 729 | 1.5231 | 0.2444 |
95
- | 1.3461 | 28.0 | 756 | 1.5218 | 0.2444 |
96
- | 1.3599 | 29.0 | 783 | 1.5209 | 0.2444 |
97
- | 1.4064 | 30.0 | 810 | 1.5203 | 0.2444 |
98
- | 1.348 | 31.0 | 837 | 1.5201 | 0.2444 |
99
- | 1.3411 | 32.0 | 864 | 1.5195 | 0.2444 |
100
- | 1.4156 | 33.0 | 891 | 1.5189 | 0.2444 |
101
- | 1.3382 | 34.0 | 918 | 1.5185 | 0.2444 |
102
- | 1.3361 | 35.0 | 945 | 1.5180 | 0.2444 |
103
- | 1.3197 | 36.0 | 972 | 1.5176 | 0.2444 |
104
- | 1.3433 | 37.0 | 999 | 1.5173 | 0.2444 |
105
- | 1.3575 | 38.0 | 1026 | 1.5170 | 0.2444 |
106
- | 1.3276 | 39.0 | 1053 | 1.5168 | 0.2444 |
107
- | 1.3024 | 40.0 | 1080 | 1.5166 | 0.2444 |
108
- | 1.3207 | 41.0 | 1107 | 1.5163 | 0.2444 |
109
- | 1.3095 | 42.0 | 1134 | 1.5162 | 0.2444 |
110
- | 1.3386 | 43.0 | 1161 | 1.5160 | 0.2444 |
111
- | 1.2808 | 44.0 | 1188 | 1.5159 | 0.2444 |
112
- | 1.3213 | 45.0 | 1215 | 1.5158 | 0.2444 |
113
- | 1.3279 | 46.0 | 1242 | 1.5157 | 0.2444 |
114
- | 1.3133 | 47.0 | 1269 | 1.5157 | 0.2444 |
115
- | 1.3138 | 48.0 | 1296 | 1.5157 | 0.2444 |
116
- | 1.3263 | 49.0 | 1323 | 1.5157 | 0.2444 |
117
- | 1.3148 | 50.0 | 1350 | 1.5157 | 0.2444 |
118
 
119
 
120
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.2
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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: 1.4758
36
+ - Accuracy: 0.2
37
 
38
  ## Model description
39
 
 
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
+ | 1.5631 | 1.0 | 27 | 1.5965 | 0.2 |
69
+ | 1.5261 | 2.0 | 54 | 1.5854 | 0.1778 |
70
+ | 1.5551 | 3.0 | 81 | 1.5758 | 0.2 |
71
+ | 1.5522 | 4.0 | 108 | 1.5674 | 0.2 |
72
+ | 1.4767 | 5.0 | 135 | 1.5601 | 0.2 |
73
+ | 1.4799 | 6.0 | 162 | 1.5535 | 0.2 |
74
+ | 1.5065 | 7.0 | 189 | 1.5472 | 0.2 |
75
+ | 1.5301 | 8.0 | 216 | 1.5418 | 0.2 |
76
+ | 1.4981 | 9.0 | 243 | 1.5367 | 0.2 |
77
+ | 1.4696 | 10.0 | 270 | 1.5320 | 0.2 |
78
+ | 1.4575 | 11.0 | 297 | 1.5277 | 0.2 |
79
+ | 1.4826 | 12.0 | 324 | 1.5238 | 0.2 |
80
+ | 1.4275 | 13.0 | 351 | 1.5196 | 0.2 |
81
+ | 1.4684 | 14.0 | 378 | 1.5162 | 0.2 |
82
+ | 1.4436 | 15.0 | 405 | 1.5135 | 0.2 |
83
+ | 1.4518 | 16.0 | 432 | 1.5107 | 0.2 |
84
+ | 1.4184 | 17.0 | 459 | 1.5080 | 0.2 |
85
+ | 1.4127 | 18.0 | 486 | 1.5055 | 0.2 |
86
+ | 1.4162 | 19.0 | 513 | 1.5030 | 0.2 |
87
+ | 1.4552 | 20.0 | 540 | 1.5007 | 0.2 |
88
+ | 1.4347 | 21.0 | 567 | 1.4985 | 0.2 |
89
+ | 1.4312 | 22.0 | 594 | 1.4966 | 0.2 |
90
+ | 1.4267 | 23.0 | 621 | 1.4951 | 0.2 |
91
+ | 1.404 | 24.0 | 648 | 1.4936 | 0.2 |
92
+ | 1.4395 | 25.0 | 675 | 1.4920 | 0.2 |
93
+ | 1.4235 | 26.0 | 702 | 1.4904 | 0.2 |
94
+ | 1.4259 | 27.0 | 729 | 1.4890 | 0.2 |
95
+ | 1.4251 | 28.0 | 756 | 1.4876 | 0.2 |
96
+ | 1.4285 | 29.0 | 783 | 1.4861 | 0.2 |
97
+ | 1.4033 | 30.0 | 810 | 1.4849 | 0.2 |
98
+ | 1.4061 | 31.0 | 837 | 1.4838 | 0.2 |
99
+ | 1.3751 | 32.0 | 864 | 1.4828 | 0.2 |
100
+ | 1.4088 | 33.0 | 891 | 1.4820 | 0.2 |
101
+ | 1.402 | 34.0 | 918 | 1.4811 | 0.2 |
102
+ | 1.4082 | 35.0 | 945 | 1.4803 | 0.2 |
103
+ | 1.4076 | 36.0 | 972 | 1.4796 | 0.2 |
104
+ | 1.3629 | 37.0 | 999 | 1.4789 | 0.2 |
105
+ | 1.3814 | 38.0 | 1026 | 1.4784 | 0.2 |
106
+ | 1.3967 | 39.0 | 1053 | 1.4779 | 0.2 |
107
+ | 1.3982 | 40.0 | 1080 | 1.4774 | 0.2 |
108
+ | 1.3817 | 41.0 | 1107 | 1.4771 | 0.2 |
109
+ | 1.4328 | 42.0 | 1134 | 1.4766 | 0.2 |
110
+ | 1.4018 | 43.0 | 1161 | 1.4763 | 0.2 |
111
+ | 1.4296 | 44.0 | 1188 | 1.4762 | 0.2 |
112
+ | 1.3826 | 45.0 | 1215 | 1.4760 | 0.2 |
113
+ | 1.4348 | 46.0 | 1242 | 1.4759 | 0.2 |
114
+ | 1.3915 | 47.0 | 1269 | 1.4758 | 0.2 |
115
+ | 1.3824 | 48.0 | 1296 | 1.4758 | 0.2 |
116
+ | 1.3767 | 49.0 | 1323 | 1.4758 | 0.2 |
117
+ | 1.374 | 50.0 | 1350 | 1.4758 | 0.2 |
118
 
119
 
120
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d466f4e4a414a66297cadff71766ade6d926af85ea5868b12de08270ae7771ea
3
  size 343086480
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:992e46d91fd9c088c93c2fb7ffd0ff4c1bd247b7fe3b84c2e7c2e6904c1a2899
3
  size 343086480