Hugging Face's logo

hkivancoral
/
hushem_1x_deit_tiny_adamax_lr0001_fold4

Image Classification
Transformers
TensorBoard
Safetensors
vit
generated_from_trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
hkivancoral commited on
Commit
8e32711
•
1 Parent(s): 96d2df9

End of training

Browse files
Files changed (3) hide show
  1. README.md +111 -0
  2. model.safetensors +1 -1
  3. runs/Nov10_12-04-43_3e3d7f37aaee/events.out.tfevents.1699617884.3e3d7f37aaee.1331.3 +2 -2
README.md ADDED
@@ -0,0 +1,111 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: facebook/deit-tiny-patch16-224
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - imagefolder
8
+ metrics:
9
+ - accuracy
10
+ model-index:
11
+ - name: hushem_1x_deit_tiny_adamax_lr0001_fold4
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: 0.8333333333333334
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
+ # hushem_1x_deit_tiny_adamax_lr0001_fold4
32
+
33
+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
34
+ It achieves the following results on the evaluation set:
35
+ - Loss: 0.5599
36
+ - Accuracy: 0.8333
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: 0.0001
56
+ - train_batch_size: 32
57
+ - eval_batch_size: 32
58
+ - seed: 42
59
+ - gradient_accumulation_steps: 4
60
+ - total_train_batch_size: 128
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: 50
65
+
66
+ ### Training results
67
+
68
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
69
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
70
+ | No log | 0.67 | 1 | 1.6749 | 0.3095 |
71
+ | No log | 2.0 | 3 | 1.3545 | 0.3333 |
72
+ | No log | 2.67 | 4 | 1.3451 | 0.2857 |
73
+ | No log | 4.0 | 6 | 1.2535 | 0.5238 |
74
+ | No log | 4.67 | 7 | 1.2290 | 0.4286 |
75
+ | No log | 6.0 | 9 | 1.1555 | 0.5 |
76
+ | 1.2457 | 6.67 | 10 | 1.0938 | 0.5 |
77
+ | 1.2457 | 8.0 | 12 | 0.9608 | 0.4762 |
78
+ | 1.2457 | 8.67 | 13 | 0.8825 | 0.5952 |
79
+ | 1.2457 | 10.0 | 15 | 0.7678 | 0.7143 |
80
+ | 1.2457 | 10.67 | 16 | 0.7184 | 0.7857 |
81
+ | 1.2457 | 12.0 | 18 | 0.6658 | 0.7619 |
82
+ | 1.2457 | 12.67 | 19 | 0.6361 | 0.7619 |
83
+ | 0.4167 | 14.0 | 21 | 0.6247 | 0.8095 |
84
+ | 0.4167 | 14.67 | 22 | 0.6111 | 0.7857 |
85
+ | 0.4167 | 16.0 | 24 | 0.5896 | 0.7857 |
86
+ | 0.4167 | 16.67 | 25 | 0.5886 | 0.7381 |
87
+ | 0.4167 | 18.0 | 27 | 0.6107 | 0.7619 |
88
+ | 0.4167 | 18.67 | 28 | 0.6198 | 0.7619 |
89
+ | 0.0627 | 20.0 | 30 | 0.6194 | 0.7619 |
90
+ | 0.0627 | 20.67 | 31 | 0.6092 | 0.7619 |
91
+ | 0.0627 | 22.0 | 33 | 0.5917 | 0.7857 |
92
+ | 0.0627 | 22.67 | 34 | 0.5871 | 0.7857 |
93
+ | 0.0627 | 24.0 | 36 | 0.5872 | 0.8095 |
94
+ | 0.0627 | 24.67 | 37 | 0.5896 | 0.8095 |
95
+ | 0.0627 | 26.0 | 39 | 0.5921 | 0.8095 |
96
+ | 0.0081 | 26.67 | 40 | 0.5908 | 0.8095 |
97
+ | 0.0081 | 28.0 | 42 | 0.5818 | 0.8095 |
98
+ | 0.0081 | 28.67 | 43 | 0.5772 | 0.8095 |
99
+ | 0.0081 | 30.0 | 45 | 0.5685 | 0.8095 |
100
+ | 0.0081 | 30.67 | 46 | 0.5654 | 0.8095 |
101
+ | 0.0081 | 32.0 | 48 | 0.5614 | 0.8333 |
102
+ | 0.0081 | 32.67 | 49 | 0.5603 | 0.8333 |
103
+ | 0.0038 | 33.33 | 50 | 0.5599 | 0.8333 |
104
+
105
+
106
+ ### Framework versions
107
+
108
+ - Transformers 4.35.0
109
+ - Pytorch 2.1.0+cu118
110
+ - Datasets 2.14.6
111
+ - Tokenizers 0.14.1
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:c8e1cea4f9ce963266e6e392a442605a252bccf53c5409c1fd3952bffa5fb3ba
3
  size 22123464
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f3bbada190f413b9d37786b5f5900cb31fd7213c2aa2bf37763084cba5be309b
3
  size 22123464
runs/Nov10_12-04-43_3e3d7f37aaee/events.out.tfevents.1699617884.3e3d7f37aaee.1331.3 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f6ad2f6f394a8eaaee3036b0bf86ecdd2cb833c904c104dd0c62ded83ed97a3e
3
- size 15480
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e89d4236cc6db9a969e11a79edf75ee57272efdc4a71c8ec2b7929e721ab0d31
3
+ size 16299