Hugging Face's logo

ongkn
/
attraction-classifier

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
Community
5
ongkn commited on
Commit
7031918
·
1 Parent(s): 3ece525

End of training

Browse files
Files changed (2) hide show
  1. README.md +12 -11
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.7912621359223301
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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 0.4868
36
- - Accuracy: 0.7913
37
 
38
  ## Model description
39
 
@@ -65,14 +65,15 @@ The following hyperparameters were used during training:
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
- | 0.5864 | 0.65 | 150 | 0.5543 | 0.7136 |
69
- | 0.5601 | 1.29 | 300 | 0.4895 | 0.7791 |
70
- | 0.5296 | 1.94 | 450 | 0.4889 | 0.75 |
71
- | 0.4706 | 2.59 | 600 | 0.4465 | 0.7888 |
72
- | 0.4401 | 3.23 | 750 | 0.4464 | 0.7888 |
73
- | 0.3888 | 3.88 | 900 | 0.4859 | 0.7791 |
74
- | 0.3365 | 4.53 | 1050 | 0.5185 | 0.7767 |
75
- | 0.3143 | 5.17 | 1200 | 0.4868 | 0.7913 |
 
76
 
77
 
78
  ### Framework versions
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.66270783847981
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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 0.7669
36
+ - Accuracy: 0.6627
37
 
38
  ## Model description
39
 
 
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
+ | 0.6253 | 0.63 | 150 | 0.5451 | 0.7245 |
69
+ | 0.486 | 1.27 | 300 | 0.5109 | 0.7411 |
70
+ | 0.5475 | 1.9 | 450 | 0.5108 | 0.7363 |
71
+ | 0.3781 | 2.53 | 600 | 0.6003 | 0.7078 |
72
+ | 0.3875 | 3.16 | 750 | 0.4860 | 0.7720 |
73
+ | 0.3855 | 3.8 | 900 | 0.4707 | 0.8100 |
74
+ | 0.3493 | 4.43 | 1050 | 0.5047 | 0.7743 |
75
+ | 0.3006 | 5.06 | 1200 | 0.5326 | 0.7625 |
76
+ | 0.3104 | 5.7 | 1350 | 0.7669 | 0.6627 |
77
 
78
 
79
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d55655ee7f761ca906f8aab2bfa186265689bc4bcdd1d7f5d7ca1593d6adacbb
3
  size 343223968
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d1f10a9fe1a927885dc7d9e3d81ddffa13ec0bafd867310a1bec7fffde5718fb
3
  size 343223968