Hugging Face's logo

clauculus
/
image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
Community
1
clauculus commited on
Commit
d173dbe
·
1 Parent(s): 475c3a3

emotion-classification

Browse files
Files changed (2) hide show
  1. README.md +114 -0
  2. pytorch_model.bin +1 -1
README.md ADDED
@@ -0,0 +1,114 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: 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: 0.49375
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
+ # 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: 1.4194
36
+ - Accuracy: 0.4938
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: 16
57
+ - eval_batch_size: 16
58
+ - seed: 42
59
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
+ - lr_scheduler_type: linear
61
+ - num_epochs: 40
62
+
63
+ ### Training results
64
+
65
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
+ | No log | 1.0 | 40 | 1.8274 | 0.325 |
68
+ | No log | 2.0 | 80 | 1.5456 | 0.4437 |
69
+ | No log | 3.0 | 120 | 1.4503 | 0.425 |
70
+ | No log | 4.0 | 160 | 1.3753 | 0.4688 |
71
+ | No log | 5.0 | 200 | 1.3046 | 0.4813 |
72
+ | No log | 6.0 | 240 | 1.2786 | 0.4875 |
73
+ | No log | 7.0 | 280 | 1.4095 | 0.4875 |
74
+ | No log | 8.0 | 320 | 1.3636 | 0.4688 |
75
+ | No log | 9.0 | 360 | 1.3518 | 0.4562 |
76
+ | No log | 10.0 | 400 | 1.4466 | 0.4688 |
77
+ | No log | 11.0 | 440 | 1.3533 | 0.5125 |
78
+ | No log | 12.0 | 480 | 1.3538 | 0.5125 |
79
+ | 1.002 | 13.0 | 520 | 1.3608 | 0.5188 |
80
+ | 1.002 | 14.0 | 560 | 1.3736 | 0.55 |
81
+ | 1.002 | 15.0 | 600 | 1.4872 | 0.4688 |
82
+ | 1.002 | 16.0 | 640 | 1.4549 | 0.525 |
83
+ | 1.002 | 17.0 | 680 | 1.4956 | 0.5062 |
84
+ | 1.002 | 18.0 | 720 | 1.5431 | 0.475 |
85
+ | 1.002 | 19.0 | 760 | 1.5045 | 0.5312 |
86
+ | 1.002 | 20.0 | 800 | 1.5330 | 0.525 |
87
+ | 1.002 | 21.0 | 840 | 1.4794 | 0.5375 |
88
+ | 1.002 | 22.0 | 880 | 1.4762 | 0.5375 |
89
+ | 1.002 | 23.0 | 920 | 1.5691 | 0.4813 |
90
+ | 1.002 | 24.0 | 960 | 1.5839 | 0.5 |
91
+ | 0.2831 | 25.0 | 1000 | 1.6461 | 0.4813 |
92
+ | 0.2831 | 26.0 | 1040 | 1.6359 | 0.4813 |
93
+ | 0.2831 | 27.0 | 1080 | 1.5603 | 0.525 |
94
+ | 0.2831 | 28.0 | 1120 | 1.5738 | 0.5 |
95
+ | 0.2831 | 29.0 | 1160 | 1.6534 | 0.4938 |
96
+ | 0.2831 | 30.0 | 1200 | 1.7387 | 0.4813 |
97
+ | 0.2831 | 31.0 | 1240 | 1.7778 | 0.4562 |
98
+ | 0.2831 | 32.0 | 1280 | 1.6399 | 0.525 |
99
+ | 0.2831 | 33.0 | 1320 | 1.6575 | 0.5437 |
100
+ | 0.2831 | 34.0 | 1360 | 1.6041 | 0.5062 |
101
+ | 0.2831 | 35.0 | 1400 | 1.8253 | 0.4813 |
102
+ | 0.2831 | 36.0 | 1440 | 1.6909 | 0.4875 |
103
+ | 0.2831 | 37.0 | 1480 | 1.6586 | 0.5437 |
104
+ | 0.1654 | 38.0 | 1520 | 1.6183 | 0.5125 |
105
+ | 0.1654 | 39.0 | 1560 | 1.6045 | 0.5188 |
106
+ | 0.1654 | 40.0 | 1600 | 1.6228 | 0.4938 |
107
+
108
+
109
+ ### Framework versions
110
+
111
+ - Transformers 4.33.2
112
+ - Pytorch 2.0.1+cu118
113
+ - Datasets 2.14.5
114
+ - Tokenizers 0.13.3
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:bc8a6bde113a26041f5389bb849938560676d2ddd2e6658928b3bdc511f5c2f8
3
  size 343287149
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:387fa3d226598b5d5e182f9b126c696e242171dd91162ee7ba559c2b69c1c6f8
3
  size 343287149