Hugging Face's logo

HorcruxNo13
/
vit-base-patch16-224

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
HorcruxNo13 commited on
Commit
5e6cd35
•
1 Parent(s): f1c1d9e

Model save

Browse files
Files changed (2) hide show
  1. README.md +23 -23
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -24,13 +24,13 @@ model-index:
24
  metrics:
25
  - name: Accuracy
26
  type: accuracy
27
- value: 0.9033333333333333
28
  - name: Precision
29
  type: precision
30
- value: 0.892075919335706
31
  - name: Recall
32
  type: recall
33
- value: 0.9033333333333333
34
  ---
35
 
36
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +40,11 @@ should probably proofread and complete it, then remove this comment. -->
40
 
41
  This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
42
  It achieves the following results on the evaluation set:
43
- - Loss: 0.2446
44
- - Accuracy: 0.9033
45
- - Precision: 0.8921
46
- - Recall: 0.9033
47
- - F1 Score: 0.8889
48
 
49
  ## Model description
50
 
@@ -78,21 +78,21 @@ The following hyperparameters were used during training:
78
 
79
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
80
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
81
- | No log | 1.0 | 4 | 0.5037 | 0.8667 | 0.8150 | 0.8667 | 0.8224 |
82
- | No log | 2.0 | 8 | 0.3500 | 0.8708 | 0.7584 | 0.8708 | 0.8107 |
83
- | No log | 3.0 | 12 | 0.3154 | 0.8708 | 0.7584 | 0.8708 | 0.8107 |
84
- | 0.5284 | 4.0 | 16 | 0.2974 | 0.8833 | 0.8659 | 0.8833 | 0.8497 |
85
- | 0.5284 | 5.0 | 20 | 0.2954 | 0.8875 | 0.8731 | 0.8875 | 0.8768 |
86
- | 0.5284 | 6.0 | 24 | 0.2721 | 0.8958 | 0.8871 | 0.8958 | 0.8716 |
87
- | 0.5284 | 7.0 | 28 | 0.2679 | 0.8875 | 0.8817 | 0.8875 | 0.8527 |
88
- | 0.3362 | 8.0 | 32 | 0.2634 | 0.8875 | 0.8817 | 0.8875 | 0.8527 |
89
- | 0.3362 | 9.0 | 36 | 0.2507 | 0.9042 | 0.8953 | 0.9042 | 0.8879 |
90
- | 0.3362 | 10.0 | 40 | 0.2439 | 0.9083 | 0.9006 | 0.9083 | 0.8941 |
91
- | 0.3362 | 11.0 | 44 | 0.2589 | 0.8917 | 0.8861 | 0.8917 | 0.8884 |
92
- | 0.3017 | 12.0 | 48 | 0.2428 | 0.9083 | 0.9005 | 0.9083 | 0.9024 |
93
- | 0.3017 | 13.0 | 52 | 0.2543 | 0.9 | 0.8949 | 0.9 | 0.8970 |
94
- | 0.3017 | 14.0 | 56 | 0.2651 | 0.8958 | 0.8944 | 0.8958 | 0.8951 |
95
- | 0.278 | 15.0 | 60 | 0.2637 | 0.8958 | 0.8944 | 0.8958 | 0.8951 |
96
 
97
 
98
  ### Framework versions
 
24
  metrics:
25
  - name: Accuracy
26
  type: accuracy
27
+ value: 0.7833333333333333
28
  - name: Precision
29
  type: precision
30
+ value: 0.7701923076923076
31
  - name: Recall
32
  type: recall
33
+ value: 0.7833333333333333
34
  ---
35
 
36
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
40
 
41
  This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
42
  It achieves the following results on the evaluation set:
43
+ - Loss: 0.4772
44
+ - Accuracy: 0.7833
45
+ - Precision: 0.7702
46
+ - Recall: 0.7833
47
+ - F1 Score: 0.7559
48
 
49
  ## Model description
50
 
 
78
 
79
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
80
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
81
+ | No log | 1.0 | 4 | 0.6010 | 0.7333 | 0.6725 | 0.7333 | 0.6280 |
82
+ | No log | 2.0 | 8 | 0.5552 | 0.7375 | 0.8067 | 0.7375 | 0.6302 |
83
+ | No log | 3.0 | 12 | 0.5450 | 0.7542 | 0.7598 | 0.7542 | 0.6782 |
84
+ | 0.576 | 4.0 | 16 | 0.5325 | 0.75 | 0.7707 | 0.75 | 0.6641 |
85
+ | 0.576 | 5.0 | 20 | 0.5234 | 0.75 | 0.7232 | 0.75 | 0.6900 |
86
+ | 0.576 | 6.0 | 24 | 0.5112 | 0.7625 | 0.7506 | 0.7625 | 0.7076 |
87
+ | 0.576 | 7.0 | 28 | 0.5082 | 0.7667 | 0.7503 | 0.7667 | 0.7221 |
88
+ | 0.4876 | 8.0 | 32 | 0.5067 | 0.7667 | 0.7466 | 0.7667 | 0.7288 |
89
+ | 0.4876 | 9.0 | 36 | 0.5091 | 0.7792 | 0.7623 | 0.7792 | 0.7528 |
90
+ | 0.4876 | 10.0 | 40 | 0.5023 | 0.7583 | 0.7393 | 0.7583 | 0.7045 |
91
+ | 0.4876 | 11.0 | 44 | 0.4911 | 0.7708 | 0.7507 | 0.7708 | 0.7435 |
92
+ | 0.4379 | 12.0 | 48 | 0.4921 | 0.7667 | 0.7487 | 0.7667 | 0.7513 |
93
+ | 0.4379 | 13.0 | 52 | 0.4906 | 0.7917 | 0.7792 | 0.7917 | 0.7680 |
94
+ | 0.4379 | 14.0 | 56 | 0.4919 | 0.7875 | 0.7731 | 0.7875 | 0.7645 |
95
+ | 0.4003 | 15.0 | 60 | 0.4929 | 0.7833 | 0.7678 | 0.7833 | 0.7587 |
96
 
97
 
98
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:c660c2306ebfbe8bdcd435543c179e96b752722602694dac615528a3b36d5279
3
  size 343268717
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e7aff6f29850e45f9d3809502ee06082d45a2c6e2e81451cb035264406def030
3
  size 343268717