sudo-s commited on
Commit
a0b5533
1 Parent(s): ba2def8

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +76 -0
README.md ADDED
@@ -0,0 +1,76 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: exper1_mesum5
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # exper1_mesum5
16
+
17
+ 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 None dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.6401
20
+ - Accuracy: 0.8278
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 0.0002
40
+ - train_batch_size: 16
41
+ - eval_batch_size: 8
42
+ - seed: 42
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - num_epochs: 4
46
+ - mixed_precision_training: Native AMP
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
+ | 3.9352 | 0.23 | 100 | 3.8550 | 0.1959 |
53
+ | 3.1536 | 0.47 | 200 | 3.1755 | 0.2888 |
54
+ | 2.6937 | 0.7 | 300 | 2.6332 | 0.4272 |
55
+ | 2.3748 | 0.93 | 400 | 2.2833 | 0.4970 |
56
+ | 1.5575 | 1.16 | 500 | 1.8712 | 0.5888 |
57
+ | 1.4063 | 1.4 | 600 | 1.6048 | 0.6314 |
58
+ | 1.1841 | 1.63 | 700 | 1.4109 | 0.6621 |
59
+ | 1.0857 | 1.86 | 800 | 1.1832 | 0.7112 |
60
+ | 0.582 | 2.09 | 900 | 1.0371 | 0.7479 |
61
+ | 0.5971 | 2.33 | 1000 | 0.9839 | 0.7462 |
62
+ | 0.4617 | 2.56 | 1100 | 0.9233 | 0.7657 |
63
+ | 0.4621 | 2.79 | 1200 | 0.8417 | 0.7828 |
64
+ | 0.2128 | 3.02 | 1300 | 0.7644 | 0.7970 |
65
+ | 0.1883 | 3.26 | 1400 | 0.7001 | 0.8183 |
66
+ | 0.1501 | 3.49 | 1500 | 0.6826 | 0.8201 |
67
+ | 0.1626 | 3.72 | 1600 | 0.6568 | 0.8254 |
68
+ | 0.1053 | 3.95 | 1700 | 0.6401 | 0.8278 |
69
+
70
+
71
+ ### Framework versions
72
+
73
+ - Transformers 4.20.1
74
+ - Pytorch 1.12.0+cu113
75
+ - Datasets 2.3.2
76
+ - Tokenizers 0.12.1