Hugging Face's logo

nqvii
/
vit_fold_1

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
 Community
nqvii commited on
Commit
e1532a9
·
verified ·
1 Parent(s): d7cb439

End of training Fold 1

Browse files
Files changed (2) hide show
  1. README.md +121 -0
  2. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: apache-2.0
4
+ base_model: google/vit-base-patch16-224
5
+ tags:
6
+ - generated_from_trainer
7
+ datasets:
8
+ - imagefolder
9
+ metrics:
10
+ - accuracy
11
+ - recall
12
+ model-index:
13
+ - name: vit_fold_1
14
+ results:
15
+ - task:
16
+ name: Image Classification
17
+ type: image-classification
18
+ dataset:
19
+ name: imagefolder
20
+ type: imagefolder
21
+ config: default
22
+ split: None
23
+ args: default
24
+ metrics:
25
+ - name: Accuracy
26
+ type: accuracy
27
+ value: 0.9689655172413794
28
+ - name: Recall
29
+ type: recall
30
+ value: 0.9693627450980392
31
+ ---
32
+
33
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
34
+ should probably proofread and complete it, then remove this comment. -->
35
+
36
+ # vit_fold_1
37
+
38
+ 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.
39
+ It achieves the following results on the evaluation set:
40
+ - Loss: 1.0952
41
+ - Accuracy: 0.9690
42
+ - F1 Score: 0.9709
43
+ - Recall: 0.9694
44
+
45
+ ## Model description
46
+
47
+ More information needed
48
+
49
+ ## Intended uses & limitations
50
+
51
+ More information needed
52
+
53
+ ## Training and evaluation data
54
+
55
+ More information needed
56
+
57
+ ## Training procedure
58
+
59
+ ### Training hyperparameters
60
+
61
+ The following hyperparameters were used during training:
62
+ - learning_rate: 1e-05
63
+ - train_batch_size: 64
64
+ - eval_batch_size: 64
65
+ - seed: 42
66
+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
67
+ - lr_scheduler_type: cosine
68
+ - lr_scheduler_warmup_steps: 150
69
+ - num_epochs: 100
70
+ - label_smoothing_factor: 0.15
71
+
72
+ ### Training results
73
+
74
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall |
75
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|
76
+ | 2.9282 | 1.0 | 19 | 2.7689 | 0.3310 | 0.2729 | 0.2884 |
77
+ | 2.7470 | 2.0 | 38 | 2.5989 | 0.4448 | 0.3540 | 0.3755 |
78
+ | 2.4449 | 3.0 | 57 | 2.3265 | 0.5931 | 0.5856 | 0.5613 |
79
+ | 2.0224 | 4.0 | 76 | 2.0013 | 0.7379 | 0.7505 | 0.7314 |
80
+ | 1.6546 | 5.0 | 95 | 1.6556 | 0.8276 | 0.8368 | 0.8288 |
81
+ | 1.3650 | 6.0 | 114 | 1.3947 | 0.9 | 0.9044 | 0.9030 |
82
+ | 1.1791 | 7.0 | 133 | 1.2692 | 0.9207 | 0.9228 | 0.9237 |
83
+ | 1.1519 | 8.0 | 152 | 1.2026 | 0.9414 | 0.9428 | 0.9398 |
84
+ | 1.1252 | 9.0 | 171 | 1.1660 | 0.9448 | 0.9465 | 0.9448 |
85
+ | 1.0789 | 10.0 | 190 | 1.1463 | 0.9483 | 0.9501 | 0.9497 |
86
+ | 1.0771 | 11.0 | 209 | 1.1329 | 0.9517 | 0.9533 | 0.9509 |
87
+ | 1.0519 | 12.0 | 228 | 1.1264 | 0.9552 | 0.9569 | 0.9533 |
88
+ | 1.0340 | 13.0 | 247 | 1.1138 | 0.9586 | 0.9610 | 0.9619 |
89
+ | 1.0224 | 14.0 | 266 | 1.1073 | 0.9655 | 0.9666 | 0.9644 |
90
+ | 0.9936 | 15.0 | 285 | 1.1274 | 0.9586 | 0.9593 | 0.9558 |
91
+ | 0.9975 | 16.0 | 304 | 1.1038 | 0.9655 | 0.9666 | 0.9644 |
92
+ | 0.9908 | 17.0 | 323 | 1.1107 | 0.9621 | 0.9631 | 0.9595 |
93
+ | 0.9870 | 18.0 | 342 | 1.1084 | 0.9655 | 0.9663 | 0.9631 |
94
+ | 0.9862 | 19.0 | 361 | 1.1079 | 0.9655 | 0.9663 | 0.9631 |
95
+ | 0.9739 | 20.0 | 380 | 1.0912 | 0.9655 | 0.9666 | 0.9644 |
96
+ | 0.9810 | 21.0 | 399 | 1.0898 | 0.9690 | 0.9698 | 0.9680 |
97
+ | 0.9865 | 22.0 | 418 | 1.0878 | 0.9655 | 0.9668 | 0.9656 |
98
+ | 0.9694 | 23.0 | 437 | 1.0842 | 0.9655 | 0.9668 | 0.9656 |
99
+ | 0.9649 | 24.0 | 456 | 1.0958 | 0.9655 | 0.9666 | 0.9644 |
100
+ | 0.9710 | 25.0 | 475 | 1.0934 | 0.9690 | 0.9698 | 0.9680 |
101
+ | 0.9672 | 26.0 | 494 | 1.0923 | 0.9655 | 0.9666 | 0.9644 |
102
+ | 0.9653 | 27.0 | 513 | 1.0932 | 0.9690 | 0.9698 | 0.9680 |
103
+ | 0.9622 | 28.0 | 532 | 1.0820 | 0.9655 | 0.9669 | 0.9668 |
104
+ | 0.9677 | 29.0 | 551 | 1.0928 | 0.9655 | 0.9666 | 0.9644 |
105
+ | 0.9639 | 30.0 | 570 | 1.0834 | 0.9655 | 0.9666 | 0.9644 |
106
+ | 0.9671 | 31.0 | 589 | 1.0952 | 0.9690 | 0.9709 | 0.9694 |
107
+ | 0.9635 | 32.0 | 608 | 1.0909 | 0.9655 | 0.9682 | 0.9694 |
108
+ | 0.9710 | 33.0 | 627 | 1.0919 | 0.9690 | 0.9709 | 0.9694 |
109
+ | 0.9614 | 34.0 | 646 | 1.0951 | 0.9655 | 0.9682 | 0.9694 |
110
+ | 0.9637 | 35.0 | 665 | 1.0940 | 0.9690 | 0.9709 | 0.9694 |
111
+ | 0.9618 | 36.0 | 684 | 1.0847 | 0.9690 | 0.9700 | 0.9693 |
112
+ | 0.9578 | 37.0 | 703 | 1.0871 | 0.9655 | 0.9668 | 0.9656 |
113
+ | 0.9646 | 38.0 | 722 | 1.0910 | 0.9655 | 0.9671 | 0.9680 |
114
+
115
+
116
+ ### Framework versions
117
+
118
+ - Transformers 5.0.0
119
+ - Pytorch 2.10.0+cu128
120
+ - Datasets 5.0.0
121
+ - Tokenizers 0.22.2
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8ffc755a4ec6a781f8ac047fc964911838076bf1363f330e1a4ed83943d92036
3
  size 343230128
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ba525488e22687cc26756c7f9192c187fc416f24c53bfd2e7d349315b7a804a4
3
  size 343230128