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rshrott
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vit-base-renovation

Image Classification
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  1. README.md +22 -22
  2. model.safetensors +1 -1
  3. runs/Mar20_02-17-56_afa5dd1e3938/events.out.tfevents.1710902001.afa5dd1e3938.399.1 +2 -2
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: 0.6712328767123288
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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the renovation dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1227
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- - Accuracy: 0.6712
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  ## Model description
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@@ -65,25 +65,25 @@ 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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- | 1.3065 | 0.2 | 25 | 1.2953 | 0.4201 |
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- | 1.1693 | 0.4 | 50 | 1.2178 | 0.4749 |
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- | 1.1812 | 0.6 | 75 | 1.1296 | 0.4932 |
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- | 1.0392 | 0.81 | 100 | 1.0653 | 0.5936 |
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- | 0.9393 | 1.01 | 125 | 1.0614 | 0.5936 |
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- | 0.7521 | 1.21 | 150 | 1.1803 | 0.5342 |
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- | 0.6482 | 1.41 | 175 | 0.9854 | 0.6210 |
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- | 0.6643 | 1.61 | 200 | 1.0757 | 0.5616 |
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- | 0.7273 | 1.81 | 225 | 1.0664 | 0.5662 |
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- | 0.6387 | 2.02 | 250 | 0.9146 | 0.6575 |
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- | 0.3924 | 2.22 | 275 | 0.9536 | 0.6530 |
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- | 0.3131 | 2.42 | 300 | 1.0534 | 0.6347 |
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- | 0.299 | 2.62 | 325 | 1.0690 | 0.6256 |
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- | 0.296 | 2.82 | 350 | 1.1816 | 0.6027 |
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- | 0.1765 | 3.02 | 375 | 0.9577 | 0.6667 |
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- | 0.1152 | 3.23 | 400 | 1.0853 | 0.6712 |
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- | 0.112 | 3.43 | 425 | 1.0749 | 0.6849 |
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- | 0.1083 | 3.63 | 450 | 1.1111 | 0.6804 |
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- | 0.0969 | 3.83 | 475 | 1.1227 | 0.6712 |
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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: 0.6666666666666666
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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the renovation dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4621
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+ - Accuracy: 0.6667
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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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+ | 0.382 | 0.2 | 25 | 1.1103 | 0.6073 |
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+ | 0.5741 | 0.4 | 50 | 1.0628 | 0.6210 |
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+ | 0.5589 | 0.6 | 75 | 1.0025 | 0.6667 |
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+ | 0.4074 | 0.81 | 100 | 1.1324 | 0.6073 |
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+ | 0.3581 | 1.01 | 125 | 1.1935 | 0.6438 |
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+ | 0.2618 | 1.21 | 150 | 1.8300 | 0.5023 |
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+ | 0.1299 | 1.41 | 175 | 1.2577 | 0.6301 |
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+ | 0.2562 | 1.61 | 200 | 1.0924 | 0.6895 |
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+ | 0.2573 | 1.81 | 225 | 1.1285 | 0.6849 |
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+ | 0.2471 | 2.02 | 250 | 1.3387 | 0.6256 |
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+ | 0.0618 | 2.22 | 275 | 1.2246 | 0.6667 |
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+ | 0.0658 | 2.42 | 300 | 1.4132 | 0.6347 |
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+ | 0.0592 | 2.62 | 325 | 1.4326 | 0.6530 |
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+ | 0.0464 | 2.82 | 350 | 1.2484 | 0.6849 |
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+ | 0.0567 | 3.02 | 375 | 1.5350 | 0.6347 |
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+ | 0.0269 | 3.23 | 400 | 1.4797 | 0.6667 |
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+ | 0.0239 | 3.43 | 425 | 1.4444 | 0.6530 |
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+ | 0.0184 | 3.63 | 450 | 1.4474 | 0.6575 |
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+ | 0.0286 | 3.83 | 475 | 1.4621 | 0.6667 |
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  ### Framework versions
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