Hugging Face's logo

sarabi1005
/
vit-base-beans_50

Image Classification
Transformers
PyTorch
vit
vision
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
1
sarabi1005 commited on
Commit
d48351c
·
1 Parent(s): cc9e982

Model save

Browse files
Files changed (2) hide show
  1. README.md +16 -13
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -2,8 +2,6 @@
2
  license: apache-2.0
3
  base_model: google/vit-base-patch16-224-in21k
4
  tags:
5
- - image-classification
6
- - vision
7
  - generated_from_trainer
8
  datasets:
9
  - imagefolder
@@ -24,7 +22,7 @@ model-index:
24
  metrics:
25
  - name: Accuracy
26
  type: accuracy
27
- value: 0.9318181818181818
28
  ---
29
 
30
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
34
 
35
  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.
36
  It achieves the following results on the evaluation set:
37
- - Loss: 0.1496
38
- - Accuracy: 0.9318
39
 
40
  ## Model description
41
 
@@ -55,22 +53,27 @@ More information needed
55
 
56
  The following hyperparameters were used during training:
57
  - learning_rate: 2e-05
58
- - train_batch_size: 16
59
- - eval_batch_size: 16
60
  - seed: 42
61
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
62
  - lr_scheduler_type: linear
63
- - num_epochs: 5.0
64
 
65
  ### Training results
66
 
67
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
68
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
69
- | No log | 1.0 | 234 | 0.1723 | 0.9303 |
70
- | No log | 2.0 | 468 | 0.2103 | 0.9242 |
71
- | 0.2573 | 3.0 | 702 | 0.1496 | 0.9318 |
72
- | 0.2573 | 4.0 | 936 | 0.1544 | 0.9364 |
73
- | 0.1879 | 5.0 | 1170 | 0.1497 | 0.9303 |
 
 
 
 
 
74
 
75
 
76
  ### Framework versions
 
2
  license: apache-2.0
3
  base_model: google/vit-base-patch16-224-in21k
4
  tags:
 
 
5
  - generated_from_trainer
6
  datasets:
7
  - imagefolder
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.9393939393939394
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: 0.1762
36
+ - Accuracy: 0.9394
37
 
38
  ## Model description
39
 
 
53
 
54
  The following hyperparameters were used during training:
55
  - learning_rate: 2e-05
56
+ - train_batch_size: 8
57
+ - eval_batch_size: 8
58
  - seed: 42
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: linear
61
+ - num_epochs: 10.0
62
 
63
  ### Training results
64
 
65
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
+ | No log | 1.0 | 468 | 0.1514 | 0.9439 |
68
+ | 0.2863 | 2.0 | 936 | 0.1917 | 0.9303 |
69
+ | 0.2377 | 3.0 | 1404 | 0.1725 | 0.9333 |
70
+ | 0.2142 | 4.0 | 1872 | 0.1782 | 0.9288 |
71
+ | 0.2058 | 5.0 | 2340 | 0.1788 | 0.9273 |
72
+ | 0.1899 | 6.0 | 2808 | 0.1824 | 0.9318 |
73
+ | 0.1838 | 7.0 | 3276 | 0.1879 | 0.9333 |
74
+ | 0.1757 | 8.0 | 3744 | 0.2391 | 0.9333 |
75
+ | 0.1852 | 9.0 | 4212 | 0.1725 | 0.9409 |
76
+ | 0.1634 | 10.0 | 4680 | 0.1762 | 0.9394 |
77
 
78
 
79
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6454794cb2f695081e863cd8e9231d5fe4727bcb9e7c34a5063f713d3558b122
3
  size 343269162
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ca69bbe844052bcfef7fb8ec6b6d7a570af0e42f1538a8f6884420b3c9d2369
3
  size 343269162