alperenoguz commited on
Commit
ed36017
1 Parent(s): 7afe503

End of training

Browse files
Files changed (1) hide show
  1. README.md +87 -0
README.md ADDED
@@ -0,0 +1,87 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: facebook/deit-base-patch16-224
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - imagefolder
8
+ metrics:
9
+ - accuracy
10
+ model-index:
11
+ - name: smids_deit_base_f1
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: test
21
+ args: default
22
+ metrics:
23
+ - name: Accuracy
24
+ type: accuracy
25
+ value: 0.8747913188647746
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
+ # smids_deit_base_f1
32
+
33
+ This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
34
+ It achieves the following results on the evaluation set:
35
+ - Loss: 0.4898
36
+ - Accuracy: 0.8748
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
+ - gradient_accumulation_steps: 4
60
+ - total_train_batch_size: 64
61
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
62
+ - lr_scheduler_type: linear
63
+ - lr_scheduler_warmup_ratio: 0.1
64
+ - num_epochs: 10
65
+
66
+ ### Training results
67
+
68
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
69
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
70
+ | 0.3398 | 1.0 | 375 | 0.4288 | 0.8164 |
71
+ | 0.2944 | 2.0 | 750 | 0.4228 | 0.8297 |
72
+ | 0.1957 | 3.0 | 1125 | 0.4014 | 0.8497 |
73
+ | 0.176 | 4.0 | 1501 | 0.4565 | 0.8514 |
74
+ | 0.1333 | 5.0 | 1876 | 0.3698 | 0.8731 |
75
+ | 0.1322 | 6.0 | 2251 | 0.5002 | 0.8481 |
76
+ | 0.0952 | 7.0 | 2626 | 0.4711 | 0.8648 |
77
+ | 0.0941 | 8.0 | 3002 | 0.4872 | 0.8698 |
78
+ | 0.0946 | 9.0 | 3377 | 0.5003 | 0.8564 |
79
+ | 0.0911 | 9.99 | 3750 | 0.4898 | 0.8748 |
80
+
81
+
82
+ ### Framework versions
83
+
84
+ - Transformers 4.32.1
85
+ - Pytorch 2.1.0+cu121
86
+ - Datasets 2.12.0
87
+ - Tokenizers 0.13.2