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hkivancoral
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smids_3x_beit_base_adamax_00001_fold3

Image Classification
Transformers
PyTorch
beit
generated_from_trainer
Eval Results
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +53 -53
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9066666666666666
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8012
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- - Accuracy: 0.9067
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  ## Model description
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@@ -65,56 +65,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.3558 | 1.0 | 225 | 0.2857 | 0.8817 |
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- | 0.2025 | 2.0 | 450 | 0.2548 | 0.9083 |
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- | 0.1598 | 3.0 | 675 | 0.2521 | 0.92 |
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- | 0.1219 | 4.0 | 900 | 0.2685 | 0.9067 |
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- | 0.1177 | 5.0 | 1125 | 0.2855 | 0.9167 |
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- | 0.0821 | 6.0 | 1350 | 0.3265 | 0.915 |
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- | 0.035 | 7.0 | 1575 | 0.3390 | 0.9133 |
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- | 0.0488 | 8.0 | 1800 | 0.3876 | 0.91 |
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- | 0.0333 | 9.0 | 2025 | 0.4069 | 0.9183 |
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- | 0.0137 | 10.0 | 2250 | 0.4823 | 0.895 |
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- | 0.0425 | 11.0 | 2475 | 0.4830 | 0.91 |
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- | 0.0131 | 12.0 | 2700 | 0.5278 | 0.9067 |
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- | 0.0362 | 13.0 | 2925 | 0.5365 | 0.91 |
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- | 0.0127 | 14.0 | 3150 | 0.5604 | 0.91 |
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- | 0.0059 | 15.0 | 3375 | 0.5988 | 0.9067 |
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- | 0.0457 | 16.0 | 3600 | 0.6291 | 0.8983 |
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- | 0.0096 | 17.0 | 3825 | 0.6121 | 0.905 |
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- | 0.0291 | 18.0 | 4050 | 0.6425 | 0.91 |
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- | 0.0279 | 19.0 | 4275 | 0.6328 | 0.9017 |
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- | 0.006 | 20.0 | 4500 | 0.7129 | 0.905 |
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- | 0.0195 | 21.0 | 4725 | 0.7320 | 0.9017 |
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- | 0.0002 | 22.0 | 4950 | 0.7512 | 0.9017 |
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- | 0.0352 | 23.0 | 5175 | 0.7248 | 0.9067 |
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- | 0.0032 | 24.0 | 5400 | 0.7414 | 0.9 |
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- | 0.0649 | 25.0 | 5625 | 0.7106 | 0.915 |
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- | 0.0454 | 26.0 | 5850 | 0.7165 | 0.91 |
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- | 0.0011 | 27.0 | 6075 | 0.7232 | 0.915 |
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- | 0.0041 | 28.0 | 6300 | 0.7095 | 0.9117 |
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- | 0.0099 | 29.0 | 6525 | 0.7308 | 0.9083 |
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- | 0.0129 | 30.0 | 6750 | 0.7895 | 0.9083 |
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- | 0.0212 | 31.0 | 6975 | 0.7650 | 0.91 |
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- | 0.0018 | 32.0 | 7200 | 0.7684 | 0.9083 |
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- | 0.0006 | 33.0 | 7425 | 0.7607 | 0.9133 |
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- | 0.0001 | 34.0 | 7650 | 0.7555 | 0.9117 |
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- | 0.0002 | 35.0 | 7875 | 0.7851 | 0.9083 |
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- | 0.0002 | 36.0 | 8100 | 0.7601 | 0.9117 |
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- | 0.0002 | 37.0 | 8325 | 0.7878 | 0.9083 |
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- | 0.0284 | 38.0 | 8550 | 0.7877 | 0.9083 |
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- | 0.0007 | 39.0 | 8775 | 0.7993 | 0.9067 |
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- | 0.002 | 40.0 | 9000 | 0.7969 | 0.91 |
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- | 0.0004 | 41.0 | 9225 | 0.8163 | 0.9083 |
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- | 0.0234 | 42.0 | 9450 | 0.7871 | 0.915 |
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- | 0.0006 | 43.0 | 9675 | 0.8006 | 0.9067 |
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- | 0.0004 | 44.0 | 9900 | 0.7989 | 0.9083 |
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- | 0.0007 | 45.0 | 10125 | 0.8058 | 0.9067 |
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- | 0.0174 | 46.0 | 10350 | 0.8151 | 0.9017 |
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- | 0.0003 | 47.0 | 10575 | 0.8093 | 0.9033 |
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- | 0.0 | 48.0 | 10800 | 0.8021 | 0.9067 |
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- | 0.0012 | 49.0 | 11025 | 0.8063 | 0.9067 |
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- | 0.0009 | 50.0 | 11250 | 0.8012 | 0.9067 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9183333333333333
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7848
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+ - Accuracy: 0.9183
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.2779 | 1.0 | 375 | 0.3054 | 0.8733 |
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+ | 0.2162 | 2.0 | 750 | 0.2359 | 0.92 |
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+ | 0.1285 | 3.0 | 1125 | 0.2539 | 0.9217 |
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+ | 0.0945 | 4.0 | 1500 | 0.2722 | 0.9233 |
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+ | 0.1011 | 5.0 | 1875 | 0.3075 | 0.92 |
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+ | 0.0628 | 6.0 | 2250 | 0.3567 | 0.9167 |
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+ | 0.0288 | 7.0 | 2625 | 0.3944 | 0.915 |
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+ | 0.0403 | 8.0 | 3000 | 0.4745 | 0.9083 |
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+ | 0.0254 | 9.0 | 3375 | 0.4777 | 0.92 |
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+ | 0.0101 | 10.0 | 3750 | 0.5260 | 0.9233 |
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+ | 0.0079 | 11.0 | 4125 | 0.5710 | 0.92 |
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+ | 0.0161 | 12.0 | 4500 | 0.5888 | 0.915 |
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+ | 0.0114 | 13.0 | 4875 | 0.6115 | 0.92 |
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+ | 0.0178 | 14.0 | 5250 | 0.6193 | 0.915 |
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+ | 0.0098 | 15.0 | 5625 | 0.6503 | 0.9183 |
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+ | 0.0165 | 16.0 | 6000 | 0.6581 | 0.9233 |
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+ | 0.0022 | 17.0 | 6375 | 0.6879 | 0.9217 |
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+ | 0.0225 | 18.0 | 6750 | 0.7059 | 0.92 |
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+ | 0.0007 | 19.0 | 7125 | 0.7568 | 0.9117 |
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+ | 0.0104 | 20.0 | 7500 | 0.6995 | 0.92 |
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+ | 0.0014 | 21.0 | 7875 | 0.7129 | 0.9183 |
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+ | 0.0053 | 22.0 | 8250 | 0.7485 | 0.9133 |
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+ | 0.0549 | 23.0 | 8625 | 0.7098 | 0.9183 |
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+ | 0.0039 | 24.0 | 9000 | 0.7046 | 0.9183 |
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+ | 0.0037 | 25.0 | 9375 | 0.7588 | 0.915 |
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+ | 0.0003 | 26.0 | 9750 | 0.7455 | 0.92 |
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+ | 0.0253 | 27.0 | 10125 | 0.8244 | 0.9033 |
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+ | 0.025 | 28.0 | 10500 | 0.7649 | 0.915 |
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+ | 0.0003 | 29.0 | 10875 | 0.7615 | 0.9183 |
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+ | 0.0276 | 30.0 | 11250 | 0.7366 | 0.92 |
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+ | 0.0005 | 31.0 | 11625 | 0.7763 | 0.915 |
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+ | 0.0305 | 32.0 | 12000 | 0.7932 | 0.91 |
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+ | 0.0001 | 33.0 | 12375 | 0.7611 | 0.9183 |
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+ | 0.0308 | 34.0 | 12750 | 0.7888 | 0.905 |
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+ | 0.0002 | 35.0 | 13125 | 0.7612 | 0.9183 |
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+ | 0.0004 | 36.0 | 13500 | 0.7891 | 0.9167 |
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+ | 0.0001 | 37.0 | 13875 | 0.7612 | 0.9183 |
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+ | 0.0 | 38.0 | 14250 | 0.7623 | 0.9167 |
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+ | 0.0009 | 39.0 | 14625 | 0.7611 | 0.9167 |
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+ | 0.0068 | 40.0 | 15000 | 0.7732 | 0.9167 |
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+ | 0.0008 | 41.0 | 15375 | 0.7647 | 0.92 |
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+ | 0.0059 | 42.0 | 15750 | 0.7690 | 0.915 |
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+ | 0.0001 | 43.0 | 16125 | 0.7709 | 0.92 |
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+ | 0.0042 | 44.0 | 16500 | 0.7831 | 0.9183 |
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+ | 0.0002 | 45.0 | 16875 | 0.7842 | 0.92 |
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+ | 0.0105 | 46.0 | 17250 | 0.7861 | 0.9183 |
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+ | 0.0007 | 47.0 | 17625 | 0.7770 | 0.915 |
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+ | 0.0 | 48.0 | 18000 | 0.7805 | 0.9183 |
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+ | 0.0 | 49.0 | 18375 | 0.7842 | 0.9183 |
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+ | 0.0 | 50.0 | 18750 | 0.7848 | 0.9183 |
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  ### Framework versions
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