hkivancoral commited on
Commit
c00b32b
1 Parent(s): 276dc71

End of training

Browse files
Files changed (2) hide show
  1. README.md +53 -53
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.9048414023372288
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: 0.8052
36
- - Accuracy: 0.9048
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
- | 0.2364 | 1.0 | 376 | 0.2730 | 0.8865 |
69
- | 0.1994 | 2.0 | 752 | 0.2517 | 0.9048 |
70
- | 0.18 | 3.0 | 1128 | 0.2778 | 0.8965 |
71
- | 0.0917 | 4.0 | 1504 | 0.3015 | 0.9015 |
72
- | 0.0814 | 5.0 | 1880 | 0.3201 | 0.8998 |
73
- | 0.0558 | 6.0 | 2256 | 0.3548 | 0.8948 |
74
- | 0.0543 | 7.0 | 2632 | 0.4154 | 0.9032 |
75
- | 0.0553 | 8.0 | 3008 | 0.4386 | 0.9032 |
76
- | 0.0406 | 9.0 | 3384 | 0.4901 | 0.8965 |
77
- | 0.0102 | 10.0 | 3760 | 0.5073 | 0.9048 |
78
- | 0.0428 | 11.0 | 4136 | 0.5930 | 0.8998 |
79
- | 0.0128 | 12.0 | 4512 | 0.5876 | 0.8982 |
80
- | 0.0227 | 13.0 | 4888 | 0.6384 | 0.8948 |
81
- | 0.0174 | 14.0 | 5264 | 0.5884 | 0.8998 |
82
- | 0.053 | 15.0 | 5640 | 0.6111 | 0.9032 |
83
- | 0.0251 | 16.0 | 6016 | 0.6363 | 0.9132 |
84
- | 0.0184 | 17.0 | 6392 | 0.6612 | 0.9082 |
85
- | 0.0084 | 18.0 | 6768 | 0.6842 | 0.9032 |
86
- | 0.0051 | 19.0 | 7144 | 0.7062 | 0.9048 |
87
- | 0.0039 | 20.0 | 7520 | 0.7133 | 0.9048 |
88
- | 0.007 | 21.0 | 7896 | 0.7339 | 0.9065 |
89
- | 0.0002 | 22.0 | 8272 | 0.6786 | 0.9098 |
90
- | 0.0093 | 23.0 | 8648 | 0.6708 | 0.9115 |
91
- | 0.0003 | 24.0 | 9024 | 0.7154 | 0.9132 |
92
- | 0.0019 | 25.0 | 9400 | 0.7405 | 0.9115 |
93
- | 0.0217 | 26.0 | 9776 | 0.7650 | 0.9015 |
94
- | 0.0004 | 27.0 | 10152 | 0.7374 | 0.9115 |
95
- | 0.0031 | 28.0 | 10528 | 0.7881 | 0.9065 |
96
- | 0.0017 | 29.0 | 10904 | 0.7483 | 0.9065 |
97
- | 0.0294 | 30.0 | 11280 | 0.7519 | 0.9149 |
98
- | 0.0001 | 31.0 | 11656 | 0.8321 | 0.8982 |
99
- | 0.008 | 32.0 | 12032 | 0.7556 | 0.9082 |
100
- | 0.0018 | 33.0 | 12408 | 0.7941 | 0.9098 |
101
- | 0.0097 | 34.0 | 12784 | 0.7661 | 0.9115 |
102
- | 0.0085 | 35.0 | 13160 | 0.8056 | 0.9032 |
103
- | 0.0018 | 36.0 | 13536 | 0.7982 | 0.9065 |
104
- | 0.0001 | 37.0 | 13912 | 0.7916 | 0.9098 |
105
- | 0.0002 | 38.0 | 14288 | 0.7866 | 0.9082 |
106
- | 0.0001 | 39.0 | 14664 | 0.7923 | 0.9132 |
107
- | 0.0001 | 40.0 | 15040 | 0.7990 | 0.9115 |
108
- | 0.001 | 41.0 | 15416 | 0.8027 | 0.9115 |
109
- | 0.0003 | 42.0 | 15792 | 0.8067 | 0.9098 |
110
- | 0.0019 | 43.0 | 16168 | 0.8213 | 0.9098 |
111
- | 0.0006 | 44.0 | 16544 | 0.8107 | 0.9048 |
112
- | 0.0229 | 45.0 | 16920 | 0.8044 | 0.9065 |
113
- | 0.0004 | 46.0 | 17296 | 0.8011 | 0.9065 |
114
- | 0.0 | 47.0 | 17672 | 0.8001 | 0.9048 |
115
- | 0.0005 | 48.0 | 18048 | 0.8019 | 0.9048 |
116
- | 0.0031 | 49.0 | 18424 | 0.8060 | 0.9048 |
117
- | 0.0037 | 50.0 | 18800 | 0.8052 | 0.9048 |
118
 
119
 
120
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.9065108514190318
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: 0.8312
36
+ - Accuracy: 0.9065
37
 
38
  ## Model description
39
 
 
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
68
+ | 0.2349 | 1.0 | 376 | 0.2964 | 0.8848 |
69
+ | 0.2022 | 2.0 | 752 | 0.2944 | 0.8932 |
70
+ | 0.1706 | 3.0 | 1128 | 0.2893 | 0.8965 |
71
+ | 0.0767 | 4.0 | 1504 | 0.3105 | 0.9015 |
72
+ | 0.0646 | 5.0 | 1880 | 0.3471 | 0.9015 |
73
+ | 0.0505 | 6.0 | 2256 | 0.3777 | 0.9015 |
74
+ | 0.0505 | 7.0 | 2632 | 0.4146 | 0.9115 |
75
+ | 0.0821 | 8.0 | 3008 | 0.4739 | 0.9115 |
76
+ | 0.0331 | 9.0 | 3384 | 0.5133 | 0.9082 |
77
+ | 0.0097 | 10.0 | 3760 | 0.5125 | 0.9065 |
78
+ | 0.0368 | 11.0 | 4136 | 0.5327 | 0.9098 |
79
+ | 0.0236 | 12.0 | 4512 | 0.6377 | 0.8881 |
80
+ | 0.0306 | 13.0 | 4888 | 0.6671 | 0.9015 |
81
+ | 0.0605 | 14.0 | 5264 | 0.6154 | 0.9048 |
82
+ | 0.0306 | 15.0 | 5640 | 0.6497 | 0.9082 |
83
+ | 0.0004 | 16.0 | 6016 | 0.6905 | 0.9098 |
84
+ | 0.0062 | 17.0 | 6392 | 0.7456 | 0.9082 |
85
+ | 0.0157 | 18.0 | 6768 | 0.7362 | 0.9048 |
86
+ | 0.0117 | 19.0 | 7144 | 0.8082 | 0.8965 |
87
+ | 0.0001 | 20.0 | 7520 | 0.7613 | 0.9098 |
88
+ | 0.0049 | 21.0 | 7896 | 0.7376 | 0.9115 |
89
+ | 0.0013 | 22.0 | 8272 | 0.7490 | 0.9098 |
90
+ | 0.0339 | 23.0 | 8648 | 0.7577 | 0.9132 |
91
+ | 0.0009 | 24.0 | 9024 | 0.7847 | 0.9098 |
92
+ | 0.0161 | 25.0 | 9400 | 0.7983 | 0.9098 |
93
+ | 0.0079 | 26.0 | 9776 | 0.7734 | 0.8948 |
94
+ | 0.0004 | 27.0 | 10152 | 0.7368 | 0.9015 |
95
+ | 0.0005 | 28.0 | 10528 | 0.7478 | 0.9098 |
96
+ | 0.0059 | 29.0 | 10904 | 0.7755 | 0.9065 |
97
+ | 0.0012 | 30.0 | 11280 | 0.8338 | 0.9082 |
98
+ | 0.0142 | 31.0 | 11656 | 0.7783 | 0.9115 |
99
+ | 0.0002 | 32.0 | 12032 | 0.7615 | 0.9165 |
100
+ | 0.0004 | 33.0 | 12408 | 0.7711 | 0.9098 |
101
+ | 0.0127 | 34.0 | 12784 | 0.7865 | 0.9165 |
102
+ | 0.0032 | 35.0 | 13160 | 0.8207 | 0.9132 |
103
+ | 0.0006 | 36.0 | 13536 | 0.8174 | 0.9098 |
104
+ | 0.0001 | 37.0 | 13912 | 0.7992 | 0.9165 |
105
+ | 0.0 | 38.0 | 14288 | 0.8040 | 0.9082 |
106
+ | 0.0001 | 39.0 | 14664 | 0.8011 | 0.9132 |
107
+ | 0.0005 | 40.0 | 15040 | 0.8052 | 0.9115 |
108
+ | 0.0001 | 41.0 | 15416 | 0.8158 | 0.9082 |
109
+ | 0.0001 | 42.0 | 15792 | 0.8157 | 0.9098 |
110
+ | 0.0 | 43.0 | 16168 | 0.8347 | 0.9065 |
111
+ | 0.0004 | 44.0 | 16544 | 0.8096 | 0.9048 |
112
+ | 0.0087 | 45.0 | 16920 | 0.8231 | 0.9065 |
113
+ | 0.0003 | 46.0 | 17296 | 0.8362 | 0.9065 |
114
+ | 0.0002 | 47.0 | 17672 | 0.8291 | 0.9098 |
115
+ | 0.0046 | 48.0 | 18048 | 0.8341 | 0.9082 |
116
+ | 0.0134 | 49.0 | 18424 | 0.8309 | 0.9065 |
117
+ | 0.0004 | 50.0 | 18800 | 0.8312 | 0.9065 |
118
 
119
 
120
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5a7f2e48c52479560b387722bc7b65e86fa19c2df892e07a4f28a32b52d00914
3
  size 343133766
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bb95c947b4c1d7f02d5199019bccfa5890cf1c2236366bb62cb1620c88dafa5d
3
  size 343133766