Hugging Face's logo

RickyIG
/
emotion_face_image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
1
RickyIG commited on
Commit
715ddf2
•
1 Parent(s): 928f15c

End of training

Browse files
Files changed (2) hide show
  1. README.md +124 -0
  2. pytorch_model.bin +1 -1
README.md ADDED
@@ -0,0 +1,124 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: google/vit-base-patch16-224-in21k
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - imagefolder
8
+ metrics:
9
+ - accuracy
10
+ model-index:
11
+ - name: emotion_face_image_classification
12
+ results:
13
+ - task:
14
+ name: Image Classification
15
+ type: image-classification
16
+ dataset:
17
+ name: imagefolder
18
+ type: imagefolder
19
+ config: default
20
+ split: train
21
+ args: default
22
+ metrics:
23
+ - name: Accuracy
24
+ type: accuracy
25
+ value: 0.55
26
+ ---
27
+
28
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
29
+ should probably proofread and complete it, then remove this comment. -->
30
+
31
+ # emotion_face_image_classification
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: 1.2556
36
+ - Accuracy: 0.55
37
+
38
+ ## Model description
39
+
40
+ More information needed
41
+
42
+ ## Intended uses & limitations
43
+
44
+ More information needed
45
+
46
+ ## Training and evaluation data
47
+
48
+ More information needed
49
+
50
+ ## Training procedure
51
+
52
+ ### Training hyperparameters
53
+
54
+ The following hyperparameters were used during training:
55
+ - learning_rate: 5e-05
56
+ - train_batch_size: 64
57
+ - eval_batch_size: 64
58
+ - seed: 42
59
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
+ - lr_scheduler_type: linear
61
+ - num_epochs: 50
62
+
63
+ ### Training results
64
+
65
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
+ | No log | 1.0 | 10 | 2.0561 | 0.1437 |
68
+ | No log | 2.0 | 20 | 1.9946 | 0.325 |
69
+ | No log | 3.0 | 30 | 1.9059 | 0.3563 |
70
+ | No log | 4.0 | 40 | 1.7640 | 0.3937 |
71
+ | No log | 5.0 | 50 | 1.6329 | 0.3812 |
72
+ | No log | 6.0 | 60 | 1.5935 | 0.375 |
73
+ | No log | 7.0 | 70 | 1.5206 | 0.4313 |
74
+ | No log | 8.0 | 80 | 1.4580 | 0.4813 |
75
+ | No log | 9.0 | 90 | 1.4422 | 0.4938 |
76
+ | No log | 10.0 | 100 | 1.4297 | 0.4437 |
77
+ | No log | 11.0 | 110 | 1.4020 | 0.5062 |
78
+ | No log | 12.0 | 120 | 1.3344 | 0.5125 |
79
+ | No log | 13.0 | 130 | 1.3541 | 0.5125 |
80
+ | No log | 14.0 | 140 | 1.2990 | 0.5125 |
81
+ | No log | 15.0 | 150 | 1.2482 | 0.5687 |
82
+ | No log | 16.0 | 160 | 1.2726 | 0.4875 |
83
+ | No log | 17.0 | 170 | 1.2523 | 0.5375 |
84
+ | No log | 18.0 | 180 | 1.2857 | 0.4813 |
85
+ | No log | 19.0 | 190 | 1.2476 | 0.5375 |
86
+ | No log | 20.0 | 200 | 1.2991 | 0.4625 |
87
+ | No log | 21.0 | 210 | 1.3108 | 0.5062 |
88
+ | No log | 22.0 | 220 | 1.3052 | 0.5 |
89
+ | No log | 23.0 | 230 | 1.2606 | 0.4813 |
90
+ | No log | 24.0 | 240 | 1.1568 | 0.5687 |
91
+ | No log | 25.0 | 250 | 1.2242 | 0.5437 |
92
+ | No log | 26.0 | 260 | 1.2031 | 0.5875 |
93
+ | No log | 27.0 | 270 | 1.1649 | 0.5625 |
94
+ | No log | 28.0 | 280 | 1.3134 | 0.4938 |
95
+ | No log | 29.0 | 290 | 1.2542 | 0.5062 |
96
+ | No log | 30.0 | 300 | 1.1542 | 0.5687 |
97
+ | No log | 31.0 | 310 | 1.1619 | 0.5625 |
98
+ | No log | 32.0 | 320 | 1.2700 | 0.5 |
99
+ | No log | 33.0 | 330 | 1.1943 | 0.55 |
100
+ | No log | 34.0 | 340 | 1.1441 | 0.575 |
101
+ | No log | 35.0 | 350 | 1.2405 | 0.5687 |
102
+ | No log | 36.0 | 360 | 1.2228 | 0.5375 |
103
+ | No log | 37.0 | 370 | 1.1598 | 0.6 |
104
+ | No log | 38.0 | 380 | 1.1894 | 0.5687 |
105
+ | No log | 39.0 | 390 | 1.2493 | 0.5188 |
106
+ | No log | 40.0 | 400 | 1.1716 | 0.5687 |
107
+ | No log | 41.0 | 410 | 1.1558 | 0.5813 |
108
+ | No log | 42.0 | 420 | 1.2529 | 0.5312 |
109
+ | No log | 43.0 | 430 | 1.2515 | 0.5625 |
110
+ | No log | 44.0 | 440 | 1.2576 | 0.5188 |
111
+ | No log | 45.0 | 450 | 1.1793 | 0.5687 |
112
+ | No log | 46.0 | 460 | 1.2252 | 0.5625 |
113
+ | No log | 47.0 | 470 | 1.1876 | 0.575 |
114
+ | No log | 48.0 | 480 | 1.2288 | 0.5375 |
115
+ | No log | 49.0 | 490 | 1.2623 | 0.5125 |
116
+ | 0.989 | 50.0 | 500 | 1.1603 | 0.5875 |
117
+
118
+
119
+ ### Framework versions
120
+
121
+ - Transformers 4.33.2
122
+ - Pytorch 2.0.1+cu118
123
+ - Datasets 2.14.5
124
+ - Tokenizers 0.13.3
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f7f411c92601a5eea9a68ad50a1a3df9a674ebe7e1b1bebf670443cef11daf7e
3
  size 343287149
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:90fbe3acc2fcd32d433196fccfb6474c126e1d45bfdcf19fe386011152dcbe35
3
  size 343287149