Hugging Face's logo

nemik
/
frost-vision-v2-google_vit-base-patch16-224-v2024-11-09

Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results
Model card Files Metrics Community
nemik commited on
Commit
476ea10
·
verified ·
1 Parent(s): 64b53e0

Model save

Browse files
Files changed (3) hide show
  1. README.md +113 -0
  2. model.safetensors +1 -1
  3. runs/Nov09_22-10-12_70708b3edc8c/events.out.tfevents.1731190217.70708b3edc8c.599.0 +2 -2
README.md ADDED
@@ -0,0 +1,113 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - webdataset
9
+ metrics:
10
+ - accuracy
11
+ - f1
12
+ - precision
13
+ - recall
14
+ model-index:
15
+ - name: frost-vision-v2-google_vit-base-patch16-224-v2024-11-09
16
+ results:
17
+ - task:
18
+ name: Image Classification
19
+ type: image-classification
20
+ dataset:
21
+ name: webdataset
22
+ type: webdataset
23
+ config: default
24
+ split: train
25
+ args: default
26
+ metrics:
27
+ - name: Accuracy
28
+ type: accuracy
29
+ value: 0.9401408450704225
30
+ - name: F1
31
+ type: f1
32
+ value: 0.8473967684021544
33
+ - name: Precision
34
+ type: precision
35
+ value: 0.8566243194192378
36
+ - name: Recall
37
+ type: recall
38
+ value: 0.8383658969804618
39
+ ---
40
+
41
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
42
+ should probably proofread and complete it, then remove this comment. -->
43
+
44
+ # frost-vision-v2-google_vit-base-patch16-224-v2024-11-09
45
+
46
+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the webdataset dataset.
47
+ It achieves the following results on the evaluation set:
48
+ - Loss: 0.2031
49
+ - Accuracy: 0.9401
50
+ - F1: 0.8474
51
+ - Precision: 0.8566
52
+ - Recall: 0.8384
53
+
54
+ ## Model description
55
+
56
+ More information needed
57
+
58
+ ## Intended uses & limitations
59
+
60
+ More information needed
61
+
62
+ ## Training and evaluation data
63
+
64
+ More information needed
65
+
66
+ ## Training procedure
67
+
68
+ ### Training hyperparameters
69
+
70
+ The following hyperparameters were used during training:
71
+ - learning_rate: 0.0002
72
+ - train_batch_size: 16
73
+ - eval_batch_size: 8
74
+ - seed: 42
75
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
76
+ - lr_scheduler_type: linear
77
+ - lr_scheduler_warmup_ratio: 0.1
78
+ - num_epochs: 30
79
+ - mixed_precision_training: Native AMP
80
+
81
+ ### Training results
82
+
83
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
84
+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
85
+ | 0.2067 | 1.4085 | 100 | 0.2229 | 0.9155 | 0.7736 | 0.8249 | 0.7282 |
86
+ | 0.1989 | 2.8169 | 200 | 0.2252 | 0.9102 | 0.7650 | 0.7950 | 0.7371 |
87
+ | 0.1364 | 4.2254 | 300 | 0.1834 | 0.9268 | 0.8163 | 0.8120 | 0.8206 |
88
+ | 0.1368 | 5.6338 | 400 | 0.1874 | 0.9268 | 0.7981 | 0.8801 | 0.7300 |
89
+ | 0.1197 | 7.0423 | 500 | 0.1769 | 0.9317 | 0.8268 | 0.8312 | 0.8224 |
90
+ | 0.099 | 8.4507 | 600 | 0.1841 | 0.9313 | 0.8189 | 0.8580 | 0.7833 |
91
+ | 0.0748 | 9.8592 | 700 | 0.1739 | 0.9359 | 0.8366 | 0.8457 | 0.8277 |
92
+ | 0.0706 | 11.2676 | 800 | 0.1762 | 0.9373 | 0.8399 | 0.8506 | 0.8295 |
93
+ | 0.0865 | 12.6761 | 900 | 0.1766 | 0.9408 | 0.8486 | 0.8611 | 0.8366 |
94
+ | 0.061 | 14.0845 | 1000 | 0.1852 | 0.9380 | 0.8445 | 0.8401 | 0.8490 |
95
+ | 0.0449 | 15.4930 | 1100 | 0.1795 | 0.9401 | 0.8482 | 0.8528 | 0.8437 |
96
+ | 0.0488 | 16.9014 | 1200 | 0.2065 | 0.9310 | 0.8253 | 0.8283 | 0.8224 |
97
+ | 0.0483 | 18.3099 | 1300 | 0.1977 | 0.9377 | 0.8427 | 0.8434 | 0.8419 |
98
+ | 0.0317 | 19.7183 | 1400 | 0.2006 | 0.9370 | 0.8395 | 0.8478 | 0.8313 |
99
+ | 0.0411 | 21.1268 | 1500 | 0.2068 | 0.9363 | 0.8368 | 0.8498 | 0.8242 |
100
+ | 0.0512 | 22.5352 | 1600 | 0.2056 | 0.9391 | 0.8446 | 0.8545 | 0.8348 |
101
+ | 0.0329 | 23.9437 | 1700 | 0.2127 | 0.9338 | 0.8294 | 0.8479 | 0.8117 |
102
+ | 0.0197 | 25.3521 | 1800 | 0.2122 | 0.9335 | 0.8286 | 0.8463 | 0.8117 |
103
+ | 0.0316 | 26.7606 | 1900 | 0.2050 | 0.9373 | 0.8399 | 0.8506 | 0.8295 |
104
+ | 0.0133 | 28.1690 | 2000 | 0.2019 | 0.9408 | 0.8495 | 0.8571 | 0.8419 |
105
+ | 0.0181 | 29.5775 | 2100 | 0.2031 | 0.9401 | 0.8474 | 0.8566 | 0.8384 |
106
+
107
+
108
+ ### Framework versions
109
+
110
+ - Transformers 4.44.2
111
+ - Pytorch 2.5.0+cu121
112
+ - Datasets 3.1.0
113
+ - Tokenizers 0.19.1
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e623b87d4027b31cee75483c2ebcb890b97dcd87962cb626660a6fd27e815c3c
3
  size 343248584
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4abbed0ebb46e4b6d1d3d29d5df27b5abc1f3b1aa63ca8f3d4ccec2fcfd98a74
3
  size 343248584
runs/Nov09_22-10-12_70708b3edc8c/events.out.tfevents.1731190217.70708b3edc8c.599.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:00d5131b23ef4311170576a97e0f33090aac7a47e7233400454eaf153cc36266
3
- size 60227
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2c9b58998f7e23cae24970ff416204ea089192357c490912c634e6ea945e0764
3
+ size 60581