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hkivancoral
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smids_5x_beit_base_adamax_00001_fold5

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 +48 -48
  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: 0.91
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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: 0.7433
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- - Accuracy: 0.91
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  ## Model description
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@@ -70,51 +70,51 @@ The following hyperparameters were used during training:
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  | 0.1226 | 3.0 | 1125 | 0.2477 | 0.9117 |
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  | 0.0876 | 4.0 | 1500 | 0.2419 | 0.92 |
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  | 0.0679 | 5.0 | 1875 | 0.3315 | 0.8983 |
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- | 0.0323 | 6.0 | 2250 | 0.3577 | 0.905 |
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- | 0.0875 | 7.0 | 2625 | 0.4077 | 0.91 |
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- | 0.0391 | 8.0 | 3000 | 0.4514 | 0.9083 |
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- | 0.0344 | 9.0 | 3375 | 0.4732 | 0.915 |
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- | 0.0171 | 10.0 | 3750 | 0.5099 | 0.9117 |
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- | 0.0599 | 11.0 | 4125 | 0.4510 | 0.9217 |
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- | 0.0163 | 12.0 | 4500 | 0.5453 | 0.9117 |
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- | 0.0023 | 13.0 | 4875 | 0.6061 | 0.9067 |
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- | 0.0277 | 14.0 | 5250 | 0.6132 | 0.9133 |
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- | 0.0137 | 15.0 | 5625 | 0.5859 | 0.9 |
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- | 0.0018 | 16.0 | 6000 | 0.5972 | 0.915 |
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- | 0.0268 | 17.0 | 6375 | 0.6520 | 0.9017 |
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- | 0.0038 | 18.0 | 6750 | 0.6210 | 0.9083 |
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- | 0.0091 | 19.0 | 7125 | 0.7252 | 0.8983 |
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- | 0.0004 | 20.0 | 7500 | 0.7082 | 0.9083 |
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- | 0.0055 | 21.0 | 7875 | 0.7412 | 0.9133 |
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- | 0.0342 | 22.0 | 8250 | 0.6826 | 0.905 |
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- | 0.0419 | 23.0 | 8625 | 0.6352 | 0.9067 |
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- | 0.0013 | 24.0 | 9000 | 0.6809 | 0.9067 |
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- | 0.0042 | 25.0 | 9375 | 0.6601 | 0.9067 |
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- | 0.0147 | 26.0 | 9750 | 0.6948 | 0.9017 |
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- | 0.0002 | 27.0 | 10125 | 0.7421 | 0.905 |
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- | 0.0091 | 28.0 | 10500 | 0.7369 | 0.9067 |
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- | 0.0118 | 29.0 | 10875 | 0.7087 | 0.8917 |
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- | 0.0094 | 30.0 | 11250 | 0.7347 | 0.91 |
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- | 0.0363 | 31.0 | 11625 | 0.7637 | 0.91 |
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- | 0.0017 | 32.0 | 12000 | 0.7652 | 0.905 |
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- | 0.0003 | 33.0 | 12375 | 0.7612 | 0.9067 |
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- | 0.0009 | 34.0 | 12750 | 0.7456 | 0.905 |
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- | 0.009 | 35.0 | 13125 | 0.7622 | 0.905 |
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- | 0.0024 | 36.0 | 13500 | 0.7430 | 0.9133 |
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- | 0.0045 | 37.0 | 13875 | 0.7578 | 0.91 |
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- | 0.0001 | 38.0 | 14250 | 0.7340 | 0.9033 |
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- | 0.0175 | 39.0 | 14625 | 0.7192 | 0.9017 |
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- | 0.0113 | 40.0 | 15000 | 0.7622 | 0.9033 |
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- | 0.0 | 41.0 | 15375 | 0.7439 | 0.9083 |
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- | 0.0 | 42.0 | 15750 | 0.7521 | 0.9083 |
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- | 0.0002 | 43.0 | 16125 | 0.7646 | 0.9083 |
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- | 0.0012 | 44.0 | 16500 | 0.7517 | 0.91 |
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- | 0.0 | 45.0 | 16875 | 0.7668 | 0.905 |
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- | 0.0005 | 46.0 | 17250 | 0.7523 | 0.9117 |
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- | 0.0161 | 47.0 | 17625 | 0.7485 | 0.91 |
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- | 0.0001 | 48.0 | 18000 | 0.7554 | 0.91 |
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- | 0.0002 | 49.0 | 18375 | 0.7466 | 0.91 |
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- | 0.0109 | 50.0 | 18750 | 0.7433 | 0.91 |
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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: 0.9083333333333333
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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: 0.7406
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+ - Accuracy: 0.9083
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  ## Model description
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  | 0.1226 | 3.0 | 1125 | 0.2477 | 0.9117 |
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  | 0.0876 | 4.0 | 1500 | 0.2419 | 0.92 |
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  | 0.0679 | 5.0 | 1875 | 0.3315 | 0.8983 |
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+ | 0.0323 | 6.0 | 2250 | 0.3576 | 0.905 |
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+ | 0.0879 | 7.0 | 2625 | 0.4064 | 0.91 |
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+ | 0.0394 | 8.0 | 3000 | 0.4497 | 0.91 |
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+ | 0.0359 | 9.0 | 3375 | 0.4692 | 0.915 |
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+ | 0.0158 | 10.0 | 3750 | 0.5082 | 0.9117 |
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+ | 0.0543 | 11.0 | 4125 | 0.4628 | 0.92 |
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+ | 0.0223 | 12.0 | 4500 | 0.5427 | 0.915 |
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+ | 0.0015 | 13.0 | 4875 | 0.6163 | 0.905 |
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+ | 0.0283 | 14.0 | 5250 | 0.6260 | 0.91 |
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+ | 0.0146 | 15.0 | 5625 | 0.5842 | 0.9083 |
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+ | 0.009 | 16.0 | 6000 | 0.6137 | 0.91 |
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+ | 0.0335 | 17.0 | 6375 | 0.6438 | 0.905 |
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+ | 0.0046 | 18.0 | 6750 | 0.6182 | 0.91 |
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+ | 0.0123 | 19.0 | 7125 | 0.7222 | 0.8983 |
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+ | 0.0002 | 20.0 | 7500 | 0.6977 | 0.9067 |
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+ | 0.0066 | 21.0 | 7875 | 0.7063 | 0.915 |
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+ | 0.0363 | 22.0 | 8250 | 0.6479 | 0.9083 |
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+ | 0.0494 | 23.0 | 8625 | 0.6537 | 0.905 |
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+ | 0.0006 | 24.0 | 9000 | 0.7370 | 0.9067 |
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+ | 0.0292 | 25.0 | 9375 | 0.6958 | 0.9 |
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+ | 0.0254 | 26.0 | 9750 | 0.7175 | 0.8983 |
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+ | 0.0001 | 27.0 | 10125 | 0.7650 | 0.9017 |
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+ | 0.0095 | 28.0 | 10500 | 0.7329 | 0.9067 |
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+ | 0.0232 | 29.0 | 10875 | 0.6879 | 0.9033 |
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+ | 0.0172 | 30.0 | 11250 | 0.7353 | 0.905 |
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+ | 0.0378 | 31.0 | 11625 | 0.7667 | 0.9117 |
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+ | 0.0068 | 32.0 | 12000 | 0.7535 | 0.9083 |
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+ | 0.0003 | 33.0 | 12375 | 0.7493 | 0.9133 |
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+ | 0.0005 | 34.0 | 12750 | 0.7396 | 0.9067 |
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+ | 0.013 | 35.0 | 13125 | 0.7540 | 0.9083 |
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+ | 0.0005 | 36.0 | 13500 | 0.7288 | 0.9083 |
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+ | 0.0073 | 37.0 | 13875 | 0.7577 | 0.9067 |
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+ | 0.0001 | 38.0 | 14250 | 0.7421 | 0.9033 |
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+ | 0.0156 | 39.0 | 14625 | 0.7370 | 0.9067 |
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+ | 0.0137 | 40.0 | 15000 | 0.7555 | 0.905 |
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+ | 0.0 | 41.0 | 15375 | 0.7434 | 0.905 |
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+ | 0.0 | 42.0 | 15750 | 0.7571 | 0.9017 |
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+ | 0.0002 | 43.0 | 16125 | 0.7615 | 0.9033 |
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+ | 0.0008 | 44.0 | 16500 | 0.7655 | 0.9033 |
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+ | 0.0 | 45.0 | 16875 | 0.7629 | 0.905 |
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+ | 0.0005 | 46.0 | 17250 | 0.7484 | 0.9117 |
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+ | 0.0132 | 47.0 | 17625 | 0.7394 | 0.9083 |
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+ | 0.0 | 48.0 | 18000 | 0.7491 | 0.91 |
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+ | 0.0001 | 49.0 | 18375 | 0.7435 | 0.91 |
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+ | 0.017 | 50.0 | 18750 | 0.7406 | 0.9083 |
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  ### Framework versions
pytorch_model.bin CHANGED
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