stevelee609 commited on
Commit
1fbd54a
1 Parent(s): 1ca3990

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +14 -7
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
- value: 0.92
25
  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
31
 
32
  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 food101 dataset.
33
  It achieves the following results on the evaluation set:
34
- - Loss: 1.1596
35
- - Accuracy: 0.92
36
 
37
  ## Model description
38
 
@@ -60,15 +60,22 @@ The following hyperparameters were used during training:
60
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
61
  - lr_scheduler_type: linear
62
  - lr_scheduler_warmup_ratio: 0.1
63
- - num_epochs: 3
64
 
65
  ### Training results
66
 
67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
68
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
69
- | 1.6627 | 0.99 | 62 | 1.6351 | 0.889 |
70
- | 1.2914 | 2.0 | 125 | 1.2724 | 0.911 |
71
- | 1.143 | 2.98 | 186 | 1.1596 | 0.92 |
 
 
 
 
 
 
 
72
 
73
 
74
  ### Framework versions
 
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
+ value: 0.939
25
  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
31
 
32
  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 food101 dataset.
33
  It achieves the following results on the evaluation set:
34
+ - Loss: 0.3194
35
+ - Accuracy: 0.939
36
 
37
  ## Model description
38
 
 
60
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
61
  - lr_scheduler_type: linear
62
  - lr_scheduler_warmup_ratio: 0.1
63
+ - num_epochs: 10
64
 
65
  ### Training results
66
 
67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
68
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
69
+ | 0.8638 | 0.99 | 62 | 0.9578 | 0.913 |
70
+ | 0.6163 | 2.0 | 125 | 0.7060 | 0.911 |
71
+ | 0.5103 | 2.99 | 187 | 0.4994 | 0.936 |
72
+ | 0.3659 | 4.0 | 250 | 0.4539 | 0.927 |
73
+ | 0.3207 | 4.99 | 312 | 0.3999 | 0.933 |
74
+ | 0.2523 | 6.0 | 375 | 0.3799 | 0.921 |
75
+ | 0.2257 | 6.99 | 437 | 0.3703 | 0.922 |
76
+ | 0.1937 | 8.0 | 500 | 0.3160 | 0.936 |
77
+ | 0.1854 | 8.99 | 562 | 0.3229 | 0.93 |
78
+ | 0.2048 | 9.92 | 620 | 0.3194 | 0.939 |
79
 
80
 
81
  ### Framework versions