Hugging Face's logo

jordyvl
/
dit_maveriq_tobacco3482_2023-07-04

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Inference Endpoints
Model card Files Community
jordyvl commited on
Commit
f84f755
•
1 Parent(s): 82fba5e

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +159 -0
README.md ADDED
@@ -0,0 +1,159 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ metrics:
5
+ - accuracy
6
+ model-index:
7
+ - name: dit_maveriq_tobacco3482_2023-07-04
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # dit_maveriq_tobacco3482_2023-07-04
15
+
16
+ This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on an unknown dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 0.2641
19
+ - Accuracy: 0.955
20
+
21
+ ## Model description
22
+
23
+ More information needed
24
+
25
+ ## Intended uses & limitations
26
+
27
+ More information needed
28
+
29
+ ## Training and evaluation data
30
+
31
+ More information needed
32
+
33
+ ## Training procedure
34
+
35
+ ### Training hyperparameters
36
+
37
+ The following hyperparameters were used during training:
38
+ - learning_rate: 2e-05
39
+ - train_batch_size: 16
40
+ - eval_batch_size: 4
41
+ - seed: 42
42
+ - gradient_accumulation_steps: 16
43
+ - total_train_batch_size: 256
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - num_epochs: 100
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
+ | No log | 0.96 | 3 | 2.0434 | 0.265 |
53
+ | No log | 1.96 | 6 | 1.9976 | 0.31 |
54
+ | No log | 2.96 | 9 | 1.7970 | 0.335 |
55
+ | No log | 3.96 | 12 | 1.6899 | 0.385 |
56
+ | No log | 4.96 | 15 | 1.6519 | 0.36 |
57
+ | No log | 5.96 | 18 | 1.5378 | 0.42 |
58
+ | No log | 6.96 | 21 | 1.4401 | 0.51 |
59
+ | No log | 7.96 | 24 | 1.3607 | 0.575 |
60
+ | No log | 8.96 | 27 | 1.2614 | 0.605 |
61
+ | No log | 9.96 | 30 | 1.1654 | 0.63 |
62
+ | No log | 10.96 | 33 | 1.0758 | 0.66 |
63
+ | No log | 11.96 | 36 | 0.9908 | 0.73 |
64
+ | No log | 12.96 | 39 | 0.9152 | 0.72 |
65
+ | No log | 13.96 | 42 | 0.8412 | 0.755 |
66
+ | No log | 14.96 | 45 | 0.7759 | 0.78 |
67
+ | No log | 15.96 | 48 | 0.7105 | 0.785 |
68
+ | No log | 16.96 | 51 | 0.6489 | 0.815 |
69
+ | No log | 17.96 | 54 | 0.6037 | 0.825 |
70
+ | No log | 18.96 | 57 | 0.5628 | 0.83 |
71
+ | No log | 19.96 | 60 | 0.5084 | 0.84 |
72
+ | No log | 20.96 | 63 | 0.4593 | 0.85 |
73
+ | No log | 21.96 | 66 | 0.4306 | 0.865 |
74
+ | No log | 22.96 | 69 | 0.4078 | 0.87 |
75
+ | No log | 23.96 | 72 | 0.3888 | 0.875 |
76
+ | No log | 24.96 | 75 | 0.3713 | 0.885 |
77
+ | No log | 25.96 | 78 | 0.3469 | 0.89 |
78
+ | No log | 26.96 | 81 | 0.3234 | 0.91 |
79
+ | No log | 27.96 | 84 | 0.3146 | 0.905 |
80
+ | No log | 28.96 | 87 | 0.3311 | 0.895 |
81
+ | No log | 29.96 | 90 | 0.3178 | 0.92 |
82
+ | No log | 30.96 | 93 | 0.3011 | 0.92 |
83
+ | No log | 31.96 | 96 | 0.2922 | 0.93 |
84
+ | No log | 32.96 | 99 | 0.2822 | 0.93 |
85
+ | No log | 33.96 | 102 | 0.2615 | 0.93 |
86
+ | No log | 34.96 | 105 | 0.2577 | 0.94 |
87
+ | No log | 35.96 | 108 | 0.2587 | 0.94 |
88
+ | No log | 36.96 | 111 | 0.2659 | 0.93 |
89
+ | No log | 37.96 | 114 | 0.2697 | 0.925 |
90
+ | No log | 38.96 | 117 | 0.2721 | 0.93 |
91
+ | No log | 39.96 | 120 | 0.2829 | 0.935 |
92
+ | No log | 40.96 | 123 | 0.2564 | 0.94 |
93
+ | No log | 41.96 | 126 | 0.2420 | 0.94 |
94
+ | No log | 42.96 | 129 | 0.2433 | 0.94 |
95
+ | No log | 43.96 | 132 | 0.2405 | 0.945 |
96
+ | No log | 44.96 | 135 | 0.2391 | 0.95 |
97
+ | No log | 45.96 | 138 | 0.2455 | 0.955 |
98
+ | No log | 46.96 | 141 | 0.2563 | 0.945 |
99
+ | No log | 47.96 | 144 | 0.2653 | 0.95 |
100
+ | No log | 48.96 | 147 | 0.2608 | 0.945 |
101
+ | No log | 49.96 | 150 | 0.2477 | 0.95 |
102
+ | No log | 50.96 | 153 | 0.2443 | 0.95 |
103
+ | No log | 51.96 | 156 | 0.2418 | 0.95 |
104
+ | No log | 52.96 | 159 | 0.2403 | 0.94 |
105
+ | No log | 53.96 | 162 | 0.2384 | 0.945 |
106
+ | No log | 54.96 | 165 | 0.2413 | 0.95 |
107
+ | No log | 55.96 | 168 | 0.2428 | 0.96 |
108
+ | No log | 56.96 | 171 | 0.2409 | 0.955 |
109
+ | No log | 57.96 | 174 | 0.2457 | 0.95 |
110
+ | No log | 58.96 | 177 | 0.2488 | 0.95 |
111
+ | No log | 59.96 | 180 | 0.2548 | 0.955 |
112
+ | No log | 60.96 | 183 | 0.2597 | 0.955 |
113
+ | No log | 61.96 | 186 | 0.2647 | 0.955 |
114
+ | No log | 62.96 | 189 | 0.2651 | 0.955 |
115
+ | No log | 63.96 | 192 | 0.2638 | 0.955 |
116
+ | No log | 64.96 | 195 | 0.2638 | 0.955 |
117
+ | No log | 65.96 | 198 | 0.2664 | 0.955 |
118
+ | No log | 66.96 | 201 | 0.2712 | 0.95 |
119
+ | No log | 67.96 | 204 | 0.2677 | 0.955 |
120
+ | No log | 68.96 | 207 | 0.2601 | 0.95 |
121
+ | No log | 69.96 | 210 | 0.2559 | 0.95 |
122
+ | No log | 70.96 | 213 | 0.2566 | 0.95 |
123
+ | No log | 71.96 | 216 | 0.2611 | 0.95 |
124
+ | No log | 72.96 | 219 | 0.2702 | 0.95 |
125
+ | No log | 73.96 | 222 | 0.2806 | 0.945 |
126
+ | No log | 74.96 | 225 | 0.2842 | 0.945 |
127
+ | No log | 75.96 | 228 | 0.2807 | 0.945 |
128
+ | No log | 76.96 | 231 | 0.2750 | 0.95 |
129
+ | No log | 77.96 | 234 | 0.2656 | 0.955 |
130
+ | No log | 78.96 | 237 | 0.2582 | 0.96 |
131
+ | No log | 79.96 | 240 | 0.2545 | 0.96 |
132
+ | No log | 80.96 | 243 | 0.2535 | 0.96 |
133
+ | No log | 81.96 | 246 | 0.2512 | 0.96 |
134
+ | No log | 82.96 | 249 | 0.2520 | 0.96 |
135
+ | No log | 83.96 | 252 | 0.2546 | 0.96 |
136
+ | No log | 84.96 | 255 | 0.2570 | 0.96 |
137
+ | No log | 85.96 | 258 | 0.2608 | 0.96 |
138
+ | No log | 86.96 | 261 | 0.2641 | 0.96 |
139
+ | No log | 87.96 | 264 | 0.2672 | 0.955 |
140
+ | No log | 88.96 | 267 | 0.2686 | 0.955 |
141
+ | No log | 89.96 | 270 | 0.2682 | 0.955 |
142
+ | No log | 90.96 | 273 | 0.2671 | 0.955 |
143
+ | No log | 91.96 | 276 | 0.2652 | 0.96 |
144
+ | No log | 92.96 | 279 | 0.2639 | 0.96 |
145
+ | No log | 93.96 | 282 | 0.2635 | 0.96 |
146
+ | No log | 94.96 | 285 | 0.2633 | 0.96 |
147
+ | No log | 95.96 | 288 | 0.2635 | 0.955 |
148
+ | No log | 96.96 | 291 | 0.2636 | 0.955 |
149
+ | No log | 97.96 | 294 | 0.2639 | 0.955 |
150
+ | No log | 98.96 | 297 | 0.2640 | 0.955 |
151
+ | No log | 99.96 | 300 | 0.2641 | 0.955 |
152
+
153
+
154
+ ### Framework versions
155
+
156
+ - Transformers 4.26.1
157
+ - Pytorch 1.13.1.post200
158
+ - Datasets 2.9.0
159
+ - Tokenizers 0.13.2