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vit-base-binary-isic-patch-16

ahishamm / vit-base-binary-isic-patch-16

Run on huggingface.co
huggingface.co
Total runs: 16
24-hour runs: 0
7-day runs: 8
30-day runs: 12
Model's Last Updated: July 01 2023
image-classification

Introduction of vit-base-binary-isic-patch-16

Model Details of vit-base-binary-isic-patch-16

vit-base-binary-isic-patch-16

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the ahishamm/isic_binary_augmented dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2665
  • Accuracy: 0.8799
  • Recall: 0.8799
  • F1: 0.8799
  • Precision: 0.8799
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4
Training results
Training Loss Epoch Step Validation Loss Accuracy Recall F1 Precision
0.3887 0.09 100 0.3201 0.8539 0.8539 0.8539 0.8539
0.2725 0.19 200 0.3208 0.8526 0.8526 0.8526 0.8526
0.2653 0.28 300 0.3113 0.8532 0.8532 0.8532 0.8532
0.2439 0.37 400 0.3156 0.8749 0.8749 0.8749 0.8749
0.2183 0.46 500 0.3145 0.8391 0.8391 0.8391 0.8391
0.2233 0.56 600 0.3083 0.8543 0.8543 0.8543 0.8543
0.2234 0.65 700 0.3757 0.8598 0.8598 0.8598 0.8598
0.1825 0.74 800 0.2665 0.8799 0.8799 0.8799 0.8799
0.1244 0.84 900 0.3088 0.8886 0.8886 0.8886 0.8886
0.1454 0.93 1000 0.4594 0.8544 0.8544 0.8544 0.8544
0.043 1.02 1100 0.3424 0.8820 0.8820 0.8820 0.8820
0.1911 1.12 1200 0.4268 0.8630 0.8630 0.8630 0.8630
0.1091 1.21 1300 0.2940 0.8779 0.8779 0.8779 0.8779
0.0426 1.3 1400 0.3423 0.8915 0.8915 0.8915 0.8915
0.0831 1.39 1500 0.4086 0.8625 0.8625 0.8625 0.8625
0.106 1.49 1600 0.3020 0.8972 0.8972 0.8972 0.8972
0.0717 1.58 1700 0.3971 0.8875 0.8875 0.8875 0.8875
0.1134 1.67 1800 0.3530 0.8924 0.8924 0.8924 0.8924
0.0702 1.77 1900 0.3878 0.8888 0.8888 0.8888 0.8888
0.0828 1.86 2000 0.3822 0.8852 0.8852 0.8852 0.8852
0.0497 1.95 2100 0.3364 0.8992 0.8992 0.8992 0.8992
0.0191 2.04 2200 0.4042 0.8925 0.8925 0.8925 0.8925
0.0388 2.14 2300 0.4485 0.8970 0.8970 0.8970 0.8970
0.0273 2.23 2400 0.3862 0.8953 0.8953 0.8953 0.8953
0.0032 2.32 2500 0.4710 0.8949 0.8949 0.8949 0.8949
0.0242 2.42 2600 0.4859 0.8938 0.8938 0.8938 0.8938
0.065 2.51 2700 0.4446 0.8983 0.8983 0.8983 0.8983
0.0258 2.6 2800 0.5354 0.8925 0.8925 0.8925 0.8925
0.001 2.7 2900 0.5201 0.8958 0.8958 0.8958 0.8958
0.0336 2.79 3000 0.5137 0.8924 0.8924 0.8924 0.8924
0.0205 2.88 3100 0.5251 0.8972 0.8972 0.8972 0.8972
0.0033 2.97 3200 0.5083 0.8907 0.8907 0.8907 0.8907
0.0009 3.07 3300 0.4909 0.9007 0.9007 0.9007 0.9007
0.0465 3.16 3400 0.5176 0.8984 0.8984 0.8984 0.8984
0.0007 3.25 3500 0.5411 0.8977 0.8977 0.8977 0.8977
0.0406 3.35 3600 0.4929 0.9008 0.9008 0.9008 0.9008
0.0016 3.44 3700 0.5065 0.8993 0.8993 0.8993 0.8993
0.0006 3.53 3800 0.5403 0.8985 0.8985 0.8985 0.8985
0.0272 3.62 3900 0.5399 0.8992 0.8992 0.8992 0.8992
0.0223 3.72 4000 0.5075 0.9044 0.9044 0.9044 0.9044
0.0006 3.81 4100 0.5432 0.8993 0.8993 0.8993 0.8993
0.0153 3.9 4200 0.5263 0.9021 0.9021 0.9021 0.9021
0.0273 4.0 4300 0.5242 0.9029 0.9029 0.9029 0.9029
Framework versions
  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3

Runs of ahishamm vit-base-binary-isic-patch-16 on huggingface.co

16
Total runs
0
24-hour runs
5
3-day runs
8
7-day runs
12
30-day runs

More Information About vit-base-binary-isic-patch-16 huggingface.co Model

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vit-base-binary-isic-patch-16 install

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ahishamm
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