Hugging Face's logo

karoladelk
/
skin_cancer_classification

Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
karoladelk commited on
Commit
951f4de
•
1 Parent(s): 10017fe

Model save

Browse files
Files changed (3) hide show
  1. README.md +148 -0
  2. model.safetensors +1 -1
  3. runs/Apr22_09-55-47_51b0a3d70cdb/events.out.tfevents.1713779772.51b0a3d70cdb.98.0 +2 -2
README.md ADDED
@@ -0,0 +1,148 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: google/vit-base-patch16-224-in21k
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ model-index:
9
+ - name: skin_cancer_classification
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # skin_cancer_classification
17
+
18
+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.9207
21
+ - Accuracy: 0.8555
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 0.0002
41
+ - train_batch_size: 32
42
+ - eval_batch_size: 16
43
+ - seed: 42
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - num_epochs: 10
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
51
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
52
+ | 0.8727 | 0.11 | 100 | 0.9507 | 0.6690 |
53
+ | 0.7811 | 0.22 | 200 | 0.8702 | 0.6843 |
54
+ | 0.7222 | 0.34 | 300 | 0.7517 | 0.7319 |
55
+ | 0.7191 | 0.45 | 400 | 0.7081 | 0.7474 |
56
+ | 0.638 | 0.56 | 500 | 0.6894 | 0.7407 |
57
+ | 0.6001 | 0.67 | 600 | 0.7046 | 0.7565 |
58
+ | 0.5818 | 0.78 | 700 | 0.7262 | 0.7422 |
59
+ | 0.5796 | 0.9 | 800 | 0.6466 | 0.7681 |
60
+ | 0.4426 | 1.01 | 900 | 0.6218 | 0.7730 |
61
+ | 0.4675 | 1.12 | 1000 | 0.6566 | 0.7569 |
62
+ | 0.4604 | 1.23 | 1100 | 0.5782 | 0.7938 |
63
+ | 0.4426 | 1.35 | 1200 | 0.5478 | 0.7996 |
64
+ | 0.3967 | 1.46 | 1300 | 0.5586 | 0.8001 |
65
+ | 0.4287 | 1.57 | 1400 | 0.5743 | 0.7948 |
66
+ | 0.4066 | 1.68 | 1500 | 0.5839 | 0.7980 |
67
+ | 0.4107 | 1.79 | 1600 | 0.5630 | 0.8032 |
68
+ | 0.3894 | 1.91 | 1700 | 0.5591 | 0.8004 |
69
+ | 0.2612 | 2.02 | 1800 | 0.5176 | 0.8173 |
70
+ | 0.346 | 2.13 | 1900 | 0.5796 | 0.7986 |
71
+ | 0.2242 | 2.24 | 2000 | 0.5196 | 0.8239 |
72
+ | 0.2262 | 2.35 | 2100 | 0.5568 | 0.8103 |
73
+ | 0.2764 | 2.47 | 2200 | 0.5428 | 0.8156 |
74
+ | 0.2795 | 2.58 | 2300 | 0.5354 | 0.8234 |
75
+ | 0.3017 | 2.69 | 2400 | 0.5231 | 0.8197 |
76
+ | 0.3295 | 2.8 | 2500 | 0.5550 | 0.8120 |
77
+ | 0.3014 | 2.91 | 2600 | 0.5151 | 0.8260 |
78
+ | 0.1332 | 3.03 | 2700 | 0.5651 | 0.8182 |
79
+ | 0.1519 | 3.14 | 2800 | 0.5824 | 0.8277 |
80
+ | 0.1537 | 3.25 | 2900 | 0.6195 | 0.8281 |
81
+ | 0.187 | 3.36 | 3000 | 0.6482 | 0.8204 |
82
+ | 0.1428 | 3.48 | 3100 | 0.5512 | 0.8463 |
83
+ | 0.1743 | 3.59 | 3200 | 0.6152 | 0.8252 |
84
+ | 0.1765 | 3.7 | 3300 | 0.5390 | 0.8418 |
85
+ | 0.1612 | 3.81 | 3400 | 0.5550 | 0.8279 |
86
+ | 0.0938 | 3.92 | 3500 | 0.6105 | 0.8380 |
87
+ | 0.0698 | 4.04 | 3600 | 0.6672 | 0.8273 |
88
+ | 0.1087 | 4.15 | 3700 | 0.6583 | 0.8184 |
89
+ | 0.0558 | 4.26 | 3800 | 0.6141 | 0.8304 |
90
+ | 0.0841 | 4.37 | 3900 | 0.6157 | 0.8377 |
91
+ | 0.0662 | 4.48 | 4000 | 0.7013 | 0.8289 |
92
+ | 0.0883 | 4.6 | 4100 | 0.7606 | 0.8180 |
93
+ | 0.0721 | 4.71 | 4200 | 0.6966 | 0.8322 |
94
+ | 0.0332 | 4.82 | 4300 | 0.7743 | 0.8189 |
95
+ | 0.0994 | 4.93 | 4400 | 0.6767 | 0.8303 |
96
+ | 0.0362 | 5.04 | 4500 | 0.7643 | 0.8321 |
97
+ | 0.0507 | 5.16 | 4600 | 0.8140 | 0.8348 |
98
+ | 0.0322 | 5.27 | 4700 | 0.7166 | 0.8397 |
99
+ | 0.0219 | 5.38 | 4800 | 0.7363 | 0.8339 |
100
+ | 0.0346 | 5.49 | 4900 | 0.7343 | 0.8435 |
101
+ | 0.0638 | 5.61 | 5000 | 0.7396 | 0.8441 |
102
+ | 0.1143 | 5.72 | 5100 | 0.8020 | 0.8338 |
103
+ | 0.024 | 5.83 | 5200 | 0.7715 | 0.8446 |
104
+ | 0.0203 | 5.94 | 5300 | 0.7485 | 0.8439 |
105
+ | 0.0172 | 6.05 | 5400 | 0.7893 | 0.8467 |
106
+ | 0.0115 | 6.17 | 5500 | 0.7671 | 0.8505 |
107
+ | 0.0628 | 6.28 | 5600 | 0.7690 | 0.8477 |
108
+ | 0.0475 | 6.39 | 5700 | 0.7534 | 0.8488 |
109
+ | 0.0193 | 6.5 | 5800 | 0.8026 | 0.8497 |
110
+ | 0.0163 | 6.61 | 5900 | 0.7703 | 0.8562 |
111
+ | 0.0232 | 6.73 | 6000 | 0.8823 | 0.8471 |
112
+ | 0.0157 | 6.84 | 6100 | 0.7953 | 0.8435 |
113
+ | 0.0211 | 6.95 | 6200 | 0.8299 | 0.8391 |
114
+ | 0.0007 | 7.06 | 6300 | 0.7862 | 0.8532 |
115
+ | 0.0085 | 7.17 | 6400 | 0.8090 | 0.8548 |
116
+ | 0.0153 | 7.29 | 6500 | 0.8183 | 0.8576 |
117
+ | 0.0031 | 7.4 | 6600 | 0.8853 | 0.8425 |
118
+ | 0.0112 | 7.51 | 6700 | 0.8415 | 0.8574 |
119
+ | 0.0012 | 7.62 | 6800 | 0.8442 | 0.8569 |
120
+ | 0.0015 | 7.74 | 6900 | 0.8475 | 0.8564 |
121
+ | 0.0043 | 7.85 | 7000 | 0.8748 | 0.8452 |
122
+ | 0.0099 | 7.96 | 7100 | 0.8873 | 0.8411 |
123
+ | 0.0008 | 8.07 | 7200 | 0.8584 | 0.8559 |
124
+ | 0.0004 | 8.18 | 7300 | 0.8598 | 0.8522 |
125
+ | 0.0004 | 8.3 | 7400 | 0.8667 | 0.8536 |
126
+ | 0.0003 | 8.41 | 7500 | 0.8667 | 0.8576 |
127
+ | 0.0073 | 8.52 | 7600 | 0.8736 | 0.8602 |
128
+ | 0.0003 | 8.63 | 7700 | 0.8760 | 0.8566 |
129
+ | 0.0007 | 8.74 | 7800 | 0.9347 | 0.8540 |
130
+ | 0.0073 | 8.86 | 7900 | 0.9070 | 0.8532 |
131
+ | 0.0002 | 8.97 | 8000 | 0.9208 | 0.8536 |
132
+ | 0.0002 | 9.08 | 8100 | 0.9304 | 0.8555 |
133
+ | 0.0003 | 9.19 | 8200 | 0.9301 | 0.8546 |
134
+ | 0.0002 | 9.3 | 8300 | 0.9298 | 0.8557 |
135
+ | 0.0002 | 9.42 | 8400 | 0.9300 | 0.8557 |
136
+ | 0.0003 | 9.53 | 8500 | 0.9283 | 0.8560 |
137
+ | 0.0002 | 9.64 | 8600 | 0.9205 | 0.8562 |
138
+ | 0.0002 | 9.75 | 8700 | 0.9216 | 0.8566 |
139
+ | 0.0002 | 9.87 | 8800 | 0.9204 | 0.8556 |
140
+ | 0.0002 | 9.98 | 8900 | 0.9207 | 0.8555 |
141
+
142
+
143
+ ### Framework versions
144
+
145
+ - Transformers 4.39.3
146
+ - Pytorch 2.1.2
147
+ - Datasets 2.18.0
148
+ - Tokenizers 0.15.2
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:777619c4c9596f175caab4228646870ee357619d6b86d92b4641971c940c3b96
3
  size 343242432
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:89454f629159f039d73284f8bacec3754c6bb380b3b5b0bb5a9b6e0d7b03125b
3
  size 343242432
runs/Apr22_09-55-47_51b0a3d70cdb/events.out.tfevents.1713779772.51b0a3d70cdb.98.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a44acba58b15f82d5ef080ab8304861207de060afec48e9f096a4b95e7524eda
3
- size 221304
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a12680fcc8577fd236c40d80d89cd32f1db5970274fafcc8a4c17c1b381670eb
3
+ size 222080