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arieg
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bw_spec_cls_4_01_noise_200_confirm

Image Classification
Transformers
TensorFlow
vit
generated_from_keras_callback
Inference Endpoints
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arieg commited on
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12a7623
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1 Parent(s): 97c5f6f

End of training

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  1. README.md +26 -26
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -15,10 +15,10 @@ probably proofread and complete it, then remove this comment. -->
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  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.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.0141
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- - Train Categorical Accuracy: 0.2486
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- - Validation Loss: 0.0136
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- - Validation Categorical Accuracy: 0.2625
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  - Epoch: 19
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  ## Model description
@@ -43,28 +43,28 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Train Loss | Train Categorical Accuracy | Validation Loss | Validation Categorical Accuracy | Epoch |
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- |:----------:|:--------------------------:|:---------------:|:-------------------------------:|:-----:|
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- | 0.5757 | 0.2444 | 0.2065 | 0.2625 | 0 |
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- | 0.1471 | 0.2486 | 0.1088 | 0.2625 | 1 |
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- | 0.0944 | 0.2486 | 0.0818 | 0.2625 | 2 |
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- | 0.0748 | 0.2486 | 0.0681 | 0.2625 | 3 |
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- | 0.0630 | 0.2486 | 0.0582 | 0.2625 | 4 |
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- | 0.0545 | 0.2486 | 0.0508 | 0.2625 | 5 |
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- | 0.0478 | 0.2486 | 0.0449 | 0.2625 | 6 |
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- | 0.0423 | 0.2486 | 0.0399 | 0.2625 | 7 |
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- | 0.0377 | 0.2486 | 0.0356 | 0.2625 | 8 |
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- | 0.0339 | 0.2486 | 0.0321 | 0.2625 | 9 |
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- | 0.0305 | 0.2486 | 0.0290 | 0.2625 | 10 |
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- | 0.0276 | 0.2486 | 0.0263 | 0.2625 | 11 |
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- | 0.0251 | 0.2486 | 0.0239 | 0.2625 | 12 |
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- | 0.0229 | 0.2486 | 0.0219 | 0.2625 | 13 |
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- | 0.0209 | 0.2486 | 0.0200 | 0.2625 | 14 |
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- | 0.0192 | 0.2486 | 0.0184 | 0.2625 | 15 |
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- | 0.0177 | 0.2486 | 0.0170 | 0.2625 | 16 |
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- | 0.0164 | 0.2486 | 0.0157 | 0.2625 | 17 |
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- | 0.0151 | 0.2486 | 0.0146 | 0.2625 | 18 |
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- | 0.0141 | 0.2486 | 0.0136 | 0.2625 | 19 |
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  ### Framework versions
 
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  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.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.0143
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+ - Train Sparse Categorical Accuracy: 1.0
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+ - Validation Loss: 0.0140
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+ - Validation Sparse Categorical Accuracy: 1.0
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  - Epoch: 19
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  ## Model description
 
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  ### Training results
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+ | Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
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+ |:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
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+ | 0.6064 | 0.9569 | 0.2224 | 1.0 | 0 |
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+ | 0.1543 | 1.0 | 0.1168 | 1.0 | 1 |
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+ | 0.0979 | 1.0 | 0.0858 | 1.0 | 2 |
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+ | 0.0769 | 1.0 | 0.0709 | 1.0 | 3 |
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+ | 0.0647 | 1.0 | 0.0603 | 1.0 | 4 |
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+ | 0.0558 | 1.0 | 0.0528 | 1.0 | 5 |
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+ | 0.0490 | 1.0 | 0.0465 | 1.0 | 6 |
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+ | 0.0434 | 1.0 | 0.0414 | 1.0 | 7 |
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+ | 0.0387 | 1.0 | 0.0369 | 1.0 | 8 |
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+ | 0.0347 | 1.0 | 0.0332 | 1.0 | 9 |
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+ | 0.0312 | 1.0 | 0.0300 | 1.0 | 10 |
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+ | 0.0282 | 1.0 | 0.0272 | 1.0 | 11 |
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+ | 0.0256 | 1.0 | 0.0248 | 1.0 | 12 |
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+ | 0.0234 | 1.0 | 0.0226 | 1.0 | 13 |
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+ | 0.0214 | 1.0 | 0.0207 | 1.0 | 14 |
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+ | 0.0196 | 1.0 | 0.0190 | 1.0 | 15 |
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+ | 0.0181 | 1.0 | 0.0176 | 1.0 | 16 |
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+ | 0.0167 | 1.0 | 0.0162 | 1.0 | 17 |
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+ | 0.0155 | 1.0 | 0.0150 | 1.0 | 18 |
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+ | 0.0143 | 1.0 | 0.0140 | 1.0 | 19 |
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  ### Framework versions
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