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Image Classification
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cvt
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  1. README.md +7 -69
  2. model.safetensors +1 -1
  3. training_args.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: 0.948051948051948
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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/cvt-13-384-22k](https://huggingface.co/microsoft/cvt-13-384-22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1695
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- - Accuracy: 0.9481
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  ## Model description
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@@ -52,78 +52,16 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 100
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- - eval_batch_size: 50
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 60
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 7 | 0.6404 | 0.6623 |
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- | No log | 2.0 | 14 | 0.5304 | 0.7273 |
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- | No log | 3.0 | 21 | 0.4551 | 0.7922 |
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- | No log | 4.0 | 28 | 0.3175 | 0.8571 |
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- | No log | 5.0 | 35 | 0.2922 | 0.8701 |
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- | No log | 6.0 | 42 | 0.2964 | 0.8701 |
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- | No log | 7.0 | 49 | 0.2839 | 0.8701 |
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- | No log | 8.0 | 56 | 0.2930 | 0.8571 |
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- | No log | 9.0 | 63 | 0.2856 | 0.8831 |
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- | No log | 10.0 | 70 | 0.2969 | 0.8831 |
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- | No log | 11.0 | 77 | 0.3002 | 0.8701 |
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- | No log | 12.0 | 84 | 0.2919 | 0.8831 |
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- | No log | 13.0 | 91 | 0.2780 | 0.8961 |
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- | No log | 14.0 | 98 | 0.2733 | 0.8831 |
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- | No log | 15.0 | 105 | 0.2489 | 0.8961 |
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- | No log | 16.0 | 112 | 0.2569 | 0.8961 |
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- | No log | 17.0 | 119 | 0.2371 | 0.9091 |
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- | No log | 18.0 | 126 | 0.2367 | 0.9091 |
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- | No log | 19.0 | 133 | 0.2297 | 0.9091 |
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- | No log | 20.0 | 140 | 0.2170 | 0.9221 |
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- | No log | 21.0 | 147 | 0.2132 | 0.9351 |
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- | No log | 22.0 | 154 | 0.2080 | 0.9351 |
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- | No log | 23.0 | 161 | 0.2010 | 0.9481 |
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- | No log | 24.0 | 168 | 0.2106 | 0.9221 |
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- | No log | 25.0 | 175 | 0.2055 | 0.9351 |
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- | No log | 26.0 | 182 | 0.1982 | 0.9481 |
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- | No log | 27.0 | 189 | 0.2105 | 0.9351 |
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- | No log | 28.0 | 196 | 0.2204 | 0.9351 |
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- | No log | 29.0 | 203 | 0.2095 | 0.9351 |
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- | No log | 30.0 | 210 | 0.2107 | 0.9221 |
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- | No log | 31.0 | 217 | 0.1808 | 0.9221 |
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- | No log | 32.0 | 224 | 0.1711 | 0.9351 |
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- | No log | 33.0 | 231 | 0.1777 | 0.9351 |
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- | No log | 34.0 | 238 | 0.1700 | 0.9351 |
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- | No log | 35.0 | 245 | 0.1743 | 0.9221 |
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- | No log | 36.0 | 252 | 0.1877 | 0.9481 |
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- | No log | 37.0 | 259 | 0.1855 | 0.9481 |
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- | No log | 38.0 | 266 | 0.1792 | 0.9481 |
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- | No log | 39.0 | 273 | 0.1607 | 0.9481 |
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- | No log | 40.0 | 280 | 0.1681 | 0.9481 |
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- | No log | 41.0 | 287 | 0.1768 | 0.9481 |
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- | No log | 42.0 | 294 | 0.1909 | 0.9481 |
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- | No log | 43.0 | 301 | 0.1812 | 0.9481 |
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- | No log | 44.0 | 308 | 0.1822 | 0.9481 |
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- | No log | 45.0 | 315 | 0.1731 | 0.9481 |
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- | No log | 46.0 | 322 | 0.1846 | 0.9351 |
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- | No log | 47.0 | 329 | 0.1846 | 0.9481 |
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- | No log | 48.0 | 336 | 0.1915 | 0.9351 |
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- | No log | 49.0 | 343 | 0.1879 | 0.9351 |
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- | No log | 50.0 | 350 | 0.1860 | 0.9351 |
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- | No log | 51.0 | 357 | 0.1907 | 0.9351 |
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- | No log | 52.0 | 364 | 0.1729 | 0.9481 |
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- | No log | 53.0 | 371 | 0.1837 | 0.9351 |
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- | No log | 54.0 | 378 | 0.1793 | 0.9351 |
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- | No log | 55.0 | 385 | 0.1783 | 0.9481 |
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- | No log | 56.0 | 392 | 0.1844 | 0.9351 |
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- | No log | 57.0 | 399 | 0.1724 | 0.9351 |
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- | No log | 58.0 | 406 | 0.1819 | 0.9351 |
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- | No log | 59.0 | 413 | 0.1792 | 0.9351 |
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- | No log | 60.0 | 420 | 0.1695 | 0.9481 |
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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: 0.935064935064935
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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/cvt-13-384-22k](https://huggingface.co/microsoft/cvt-13-384-22k) on the imagefolder dataset.
34
  It achieves the following results on the evaluation set:
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+ - Loss: 0.1983
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+ - Accuracy: 0.9351
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 400
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+ - eval_batch_size: 100
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 40
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  ### Training results
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  ### Framework versions
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