polejowska commited on
Commit
c09ef4b
1 Parent(s): a86f152

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +9 -6
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
- value: 0.9166666666666666
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 [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
33
  It achieves the following results on the evaluation set:
34
- - Loss: 0.2592
35
- - Accuracy: 0.9167
36
 
37
  ## Model description
38
 
@@ -60,14 +60,17 @@ 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: 2
64
 
65
  ### Training results
66
 
67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
68
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
69
- | 0.4904 | 0.98 | 33 | 0.3857 | 0.8783 |
70
- | 0.2188 | 1.98 | 66 | 0.2592 | 0.9167 |
 
 
 
71
 
72
 
73
  ### Framework versions
 
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
+ value: 0.9775132275132276
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 [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
33
  It achieves the following results on the evaluation set:
34
+ - Loss: 0.0918
35
+ - Accuracy: 0.9775
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: 5
64
 
65
  ### Training results
66
 
67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
68
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
69
+ | 0.6233 | 0.98 | 33 | 0.3001 | 0.9101 |
70
+ | 0.1958 | 1.98 | 66 | 0.1287 | 0.9643 |
71
+ | 0.1212 | 2.98 | 99 | 0.1109 | 0.9709 |
72
+ | 0.0734 | 3.98 | 132 | 0.1179 | 0.9643 |
73
+ | 0.0457 | 4.98 | 165 | 0.0918 | 0.9775 |
74
 
75
 
76
  ### Framework versions