Hugging Face's logo

hkivancoral
/
smids_1x_deit_small_rms_0001_fold5

Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
hkivancoral commited on
Commit
088a81b
·
1 Parent(s): e406f54

End of training

Browse files
Files changed (2) hide show
  1. README.md +54 -54
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.8566666666666667
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 [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 1.3208
36
- - Accuracy: 0.8567
37
 
38
  ## Model description
39
 
@@ -52,7 +52,7 @@ More information needed
52
  ### Training hyperparameters
53
 
54
  The following hyperparameters were used during training:
55
- - learning_rate: 0.0001
56
  - train_batch_size: 32
57
  - eval_batch_size: 32
58
  - seed: 42
@@ -65,56 +65,56 @@ The following hyperparameters were used during training:
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
- | 1.113 | 1.0 | 75 | 1.0245 | 0.4567 |
69
- | 0.7613 | 2.0 | 150 | 0.8862 | 0.5517 |
70
- | 0.703 | 3.0 | 225 | 0.8340 | 0.635 |
71
- | 0.6337 | 4.0 | 300 | 0.6263 | 0.7617 |
72
- | 0.5537 | 5.0 | 375 | 0.5021 | 0.8117 |
73
- | 0.3992 | 6.0 | 450 | 0.5968 | 0.7833 |
74
- | 0.3572 | 7.0 | 525 | 0.4874 | 0.8217 |
75
- | 0.3109 | 8.0 | 600 | 0.5263 | 0.83 |
76
- | 0.21 | 9.0 | 675 | 0.5912 | 0.8117 |
77
- | 0.1479 | 10.0 | 750 | 0.5339 | 0.84 |
78
- | 0.2099 | 11.0 | 825 | 0.7094 | 0.7833 |
79
- | 0.1541 | 12.0 | 900 | 0.6539 | 0.83 |
80
- | 0.1509 | 13.0 | 975 | 0.6516 | 0.8317 |
81
- | 0.0981 | 14.0 | 1050 | 0.7617 | 0.835 |
82
- | 0.0847 | 15.0 | 1125 | 1.0399 | 0.7983 |
83
- | 0.0793 | 16.0 | 1200 | 0.8999 | 0.835 |
84
- | 0.0165 | 17.0 | 1275 | 1.0092 | 0.835 |
85
- | 0.1094 | 18.0 | 1350 | 0.9563 | 0.83 |
86
- | 0.0659 | 19.0 | 1425 | 1.0651 | 0.8067 |
87
- | 0.08 | 20.0 | 1500 | 1.1637 | 0.8217 |
88
- | 0.0353 | 21.0 | 1575 | 1.0107 | 0.83 |
89
- | 0.0204 | 22.0 | 1650 | 1.0300 | 0.8333 |
90
- | 0.0199 | 23.0 | 1725 | 1.0667 | 0.8483 |
91
- | 0.024 | 24.0 | 1800 | 1.1535 | 0.8433 |
92
- | 0.0243 | 25.0 | 1875 | 0.9917 | 0.85 |
93
- | 0.0461 | 26.0 | 1950 | 0.9503 | 0.84 |
94
- | 0.0125 | 27.0 | 2025 | 1.1590 | 0.8367 |
95
- | 0.0524 | 28.0 | 2100 | 1.1535 | 0.8383 |
96
- | 0.0218 | 29.0 | 2175 | 1.1597 | 0.835 |
97
- | 0.0034 | 30.0 | 2250 | 1.1042 | 0.8483 |
98
- | 0.1072 | 31.0 | 2325 | 1.1051 | 0.84 |
99
- | 0.0006 | 32.0 | 2400 | 1.1382 | 0.835 |
100
- | 0.0178 | 33.0 | 2475 | 1.1829 | 0.845 |
101
- | 0.0001 | 34.0 | 2550 | 1.1434 | 0.8483 |
102
- | 0.0054 | 35.0 | 2625 | 1.0922 | 0.8583 |
103
- | 0.0 | 36.0 | 2700 | 1.0926 | 0.86 |
104
- | 0.0045 | 37.0 | 2775 | 1.2343 | 0.8317 |
105
- | 0.0054 | 38.0 | 2850 | 1.1645 | 0.8433 |
106
- | 0.0 | 39.0 | 2925 | 1.2526 | 0.8433 |
107
- | 0.0 | 40.0 | 3000 | 1.2634 | 0.85 |
108
- | 0.0032 | 41.0 | 3075 | 1.2862 | 0.8483 |
109
- | 0.0 | 42.0 | 3150 | 1.2802 | 0.8483 |
110
- | 0.0078 | 43.0 | 3225 | 1.2893 | 0.85 |
111
- | 0.0 | 44.0 | 3300 | 1.2963 | 0.8483 |
112
- | 0.0022 | 45.0 | 3375 | 1.2999 | 0.8533 |
113
- | 0.0 | 46.0 | 3450 | 1.3031 | 0.85 |
114
- | 0.0057 | 47.0 | 3525 | 1.3122 | 0.8567 |
115
- | 0.005 | 48.0 | 3600 | 1.3153 | 0.8567 |
116
- | 0.0 | 49.0 | 3675 | 1.3203 | 0.8567 |
117
- | 0.0042 | 50.0 | 3750 | 1.3208 | 0.8567 |
118
 
119
 
120
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.7483333333333333
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 [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 1.2122
36
+ - Accuracy: 0.7483
37
 
38
  ## Model description
39
 
 
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
 
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
+ | 1.0524 | 1.0 | 75 | 0.9597 | 0.445 |
69
+ | 1.1247 | 2.0 | 150 | 1.1111 | 0.3367 |
70
+ | 0.979 | 3.0 | 225 | 0.9077 | 0.5 |
71
+ | 0.8898 | 4.0 | 300 | 0.8740 | 0.52 |
72
+ | 0.8714 | 5.0 | 375 | 0.9443 | 0.4433 |
73
+ | 0.8755 | 6.0 | 450 | 0.7908 | 0.5917 |
74
+ | 0.8257 | 7.0 | 525 | 0.8028 | 0.5817 |
75
+ | 0.7602 | 8.0 | 600 | 0.8435 | 0.605 |
76
+ | 0.7994 | 9.0 | 675 | 0.7977 | 0.6117 |
77
+ | 0.7424 | 10.0 | 750 | 0.7850 | 0.6117 |
78
+ | 0.8101 | 11.0 | 825 | 0.7616 | 0.6233 |
79
+ | 0.7712 | 12.0 | 900 | 0.7668 | 0.6367 |
80
+ | 0.7209 | 13.0 | 975 | 0.8101 | 0.62 |
81
+ | 0.7215 | 14.0 | 1050 | 0.7936 | 0.62 |
82
+ | 0.7097 | 15.0 | 1125 | 0.7953 | 0.61 |
83
+ | 0.7072 | 16.0 | 1200 | 0.7924 | 0.6317 |
84
+ | 0.7074 | 17.0 | 1275 | 0.7452 | 0.6667 |
85
+ | 0.6856 | 18.0 | 1350 | 0.7477 | 0.6717 |
86
+ | 0.6768 | 19.0 | 1425 | 0.7216 | 0.6783 |
87
+ | 0.6919 | 20.0 | 1500 | 0.7445 | 0.68 |
88
+ | 0.6145 | 21.0 | 1575 | 0.7497 | 0.6533 |
89
+ | 0.5852 | 22.0 | 1650 | 0.7462 | 0.7083 |
90
+ | 0.625 | 23.0 | 1725 | 0.7496 | 0.675 |
91
+ | 0.549 | 24.0 | 1800 | 0.7315 | 0.7067 |
92
+ | 0.5773 | 25.0 | 1875 | 0.7055 | 0.7033 |
93
+ | 0.5746 | 26.0 | 1950 | 0.6982 | 0.7283 |
94
+ | 0.5717 | 27.0 | 2025 | 0.7187 | 0.705 |
95
+ | 0.5927 | 28.0 | 2100 | 0.6996 | 0.7183 |
96
+ | 0.5713 | 29.0 | 2175 | 0.6989 | 0.7217 |
97
+ | 0.5709 | 30.0 | 2250 | 0.7204 | 0.7267 |
98
+ | 0.5164 | 31.0 | 2325 | 0.7778 | 0.705 |
99
+ | 0.5059 | 32.0 | 2400 | 0.7021 | 0.73 |
100
+ | 0.5725 | 33.0 | 2475 | 0.6873 | 0.735 |
101
+ | 0.4839 | 34.0 | 2550 | 0.6931 | 0.745 |
102
+ | 0.4617 | 35.0 | 2625 | 0.7517 | 0.75 |
103
+ | 0.4294 | 36.0 | 2700 | 0.8099 | 0.7533 |
104
+ | 0.3749 | 37.0 | 2775 | 0.7255 | 0.75 |
105
+ | 0.4163 | 38.0 | 2850 | 0.7476 | 0.7533 |
106
+ | 0.3565 | 39.0 | 2925 | 0.8354 | 0.735 |
107
+ | 0.382 | 40.0 | 3000 | 0.8201 | 0.7467 |
108
+ | 0.3261 | 41.0 | 3075 | 0.8167 | 0.7567 |
109
+ | 0.4372 | 42.0 | 3150 | 0.8428 | 0.7267 |
110
+ | 0.3484 | 43.0 | 3225 | 0.8996 | 0.74 |
111
+ | 0.3261 | 44.0 | 3300 | 0.9207 | 0.735 |
112
+ | 0.2963 | 45.0 | 3375 | 1.0220 | 0.7283 |
113
+ | 0.2143 | 46.0 | 3450 | 0.9860 | 0.755 |
114
+ | 0.2551 | 47.0 | 3525 | 1.1473 | 0.7333 |
115
+ | 0.1675 | 48.0 | 3600 | 1.1351 | 0.735 |
116
+ | 0.1431 | 49.0 | 3675 | 1.1685 | 0.75 |
117
+ | 0.1393 | 50.0 | 3750 | 1.2122 | 0.7483 |
118
 
119
 
120
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5ec390aef3fde13ebecc7ec3767476753d2e3889dc73185a7cfc6843ef17af36
3
  size 86690164
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9c9a815fbaece42b0112f46084d185954ce326b9ff1f2e2c4e788a2d0b045678
3
  size 86690164