aaraki commited on
Commit
faa204e
1 Parent(s): 18ef474

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +75 -0
README.md ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - cifar10
7
+ metrics:
8
+ - accuracy
9
+ model-index:
10
+ - name: vit-base-patch16-224-in21k-finetuned-cifar10
11
+ results:
12
+ - task:
13
+ name: Image Classification
14
+ type: image-classification
15
+ dataset:
16
+ name: cifar10
17
+ type: cifar10
18
+ args: plain_text
19
+ metrics:
20
+ - name: Accuracy
21
+ type: accuracy
22
+ value: 0.9788
23
+ ---
24
+
25
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
26
+ should probably proofread and complete it, then remove this comment. -->
27
+
28
+ # vit-base-patch16-224-in21k-finetuned-cifar10
29
+
30
+ 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 cifar10 dataset.
31
+ It achieves the following results on the evaluation set:
32
+ - Loss: 0.2564
33
+ - Accuracy: 0.9788
34
+
35
+ ## Model description
36
+
37
+ More information needed
38
+
39
+ ## Intended uses & limitations
40
+
41
+ More information needed
42
+
43
+ ## Training and evaluation data
44
+
45
+ More information needed
46
+
47
+ ## Training procedure
48
+
49
+ ### Training hyperparameters
50
+
51
+ The following hyperparameters were used during training:
52
+ - learning_rate: 5e-05
53
+ - train_batch_size: 32
54
+ - eval_batch_size: 32
55
+ - seed: 42
56
+ - gradient_accumulation_steps: 4
57
+ - total_train_batch_size: 128
58
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
59
+ - lr_scheduler_type: linear
60
+ - lr_scheduler_warmup_ratio: 0.1
61
+ - num_epochs: 1
62
+
63
+ ### Training results
64
+
65
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
66
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
67
+ | 0.4291 | 1.0 | 390 | 0.2564 | 0.9788 |
68
+
69
+
70
+ ### Framework versions
71
+
72
+ - Transformers 4.17.0
73
+ - Pytorch 1.10.0+cu111
74
+ - Datasets 2.0.0
75
+ - Tokenizers 0.11.6