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hkivancoral
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hushem_conflu_deneme_f1

Image Classification
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  1. README.md +54 -14
  2. model.safetensors +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: 0.3111111111111111
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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 [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.8033
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- - Accuracy: 0.3111
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  ## Model description
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@@ -59,22 +59,62 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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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 | 6 | 1.6574 | 0.2444 |
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- | 1.7719 | 2.0 | 12 | 1.3830 | 0.2444 |
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- | 1.7719 | 3.0 | 18 | 1.5601 | 0.2444 |
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- | 1.2648 | 4.0 | 24 | 1.4049 | 0.4667 |
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- | 1.1338 | 5.0 | 30 | 1.4959 | 0.2444 |
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- | 1.1338 | 6.0 | 36 | 1.4718 | 0.3556 |
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- | 0.9412 | 7.0 | 42 | 1.5897 | 0.3778 |
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- | 0.9412 | 8.0 | 48 | 1.8123 | 0.3111 |
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- | 0.7973 | 9.0 | 54 | 1.8033 | 0.3111 |
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- | 0.7285 | 10.0 | 60 | 1.8033 | 0.3111 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.4222222222222222
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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 [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.1726
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+ - Accuracy: 0.4222
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 50
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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 | 6 | 1.4791 | 0.3333 |
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+ | 2.0372 | 2.0 | 12 | 1.3991 | 0.2444 |
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+ | 2.0372 | 3.0 | 18 | 1.9327 | 0.2444 |
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+ | 1.2524 | 4.0 | 24 | 1.4584 | 0.3556 |
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+ | 1.1547 | 5.0 | 30 | 1.3317 | 0.3556 |
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+ | 1.1547 | 6.0 | 36 | 1.9319 | 0.3333 |
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+ | 0.8748 | 7.0 | 42 | 1.3603 | 0.4222 |
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+ | 0.8748 | 8.0 | 48 | 1.0979 | 0.5333 |
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+ | 0.8902 | 9.0 | 54 | 1.9103 | 0.4222 |
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+ | 0.6653 | 10.0 | 60 | 2.0004 | 0.3778 |
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+ | 0.6653 | 11.0 | 66 | 2.0962 | 0.4 |
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+ | 0.5253 | 12.0 | 72 | 1.2246 | 0.5111 |
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+ | 0.5253 | 13.0 | 78 | 1.6731 | 0.4889 |
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+ | 0.5223 | 14.0 | 84 | 2.1516 | 0.4 |
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+ | 0.2968 | 15.0 | 90 | 2.5065 | 0.4 |
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+ | 0.2968 | 16.0 | 96 | 2.0657 | 0.4444 |
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+ | 0.4394 | 17.0 | 102 | 1.5876 | 0.4667 |
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+ | 0.4394 | 18.0 | 108 | 2.1433 | 0.4 |
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+ | 0.2725 | 19.0 | 114 | 1.4220 | 0.5556 |
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+ | 0.1718 | 20.0 | 120 | 1.7558 | 0.4667 |
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+ | 0.1718 | 21.0 | 126 | 2.3734 | 0.4667 |
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+ | 0.0642 | 22.0 | 132 | 2.9683 | 0.4667 |
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+ | 0.0642 | 23.0 | 138 | 2.9217 | 0.4889 |
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+ | 0.0435 | 24.0 | 144 | 3.4732 | 0.4667 |
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+ | 0.0409 | 25.0 | 150 | 3.8797 | 0.4667 |
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+ | 0.0409 | 26.0 | 156 | 4.3387 | 0.4444 |
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+ | 0.0418 | 27.0 | 162 | 3.9839 | 0.4444 |
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+ | 0.0418 | 28.0 | 168 | 4.5122 | 0.4444 |
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+ | 0.0035 | 29.0 | 174 | 4.2517 | 0.4444 |
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+ | 0.0006 | 30.0 | 180 | 3.9958 | 0.4444 |
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+ | 0.0006 | 31.0 | 186 | 3.9647 | 0.4444 |
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+ | 0.0004 | 32.0 | 192 | 3.9928 | 0.4444 |
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+ | 0.0004 | 33.0 | 198 | 4.0376 | 0.4222 |
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+ | 0.0003 | 34.0 | 204 | 4.0736 | 0.4222 |
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+ | 0.0002 | 35.0 | 210 | 4.1046 | 0.4222 |
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+ | 0.0002 | 36.0 | 216 | 4.1284 | 0.4222 |
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+ | 0.0002 | 37.0 | 222 | 4.1466 | 0.4222 |
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+ | 0.0002 | 38.0 | 228 | 4.1585 | 0.4222 |
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+ | 0.0002 | 39.0 | 234 | 4.1664 | 0.4222 |
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+ | 0.0002 | 40.0 | 240 | 4.1704 | 0.4222 |
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+ | 0.0002 | 41.0 | 246 | 4.1721 | 0.4222 |
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+ | 0.0002 | 42.0 | 252 | 4.1726 | 0.4222 |
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+ | 0.0002 | 43.0 | 258 | 4.1726 | 0.4222 |
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+ | 0.0002 | 44.0 | 264 | 4.1726 | 0.4222 |
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+ | 0.0002 | 45.0 | 270 | 4.1726 | 0.4222 |
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+ | 0.0002 | 46.0 | 276 | 4.1726 | 0.4222 |
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+ | 0.0002 | 47.0 | 282 | 4.1726 | 0.4222 |
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+ | 0.0002 | 48.0 | 288 | 4.1726 | 0.4222 |
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+ | 0.0002 | 49.0 | 294 | 4.1726 | 0.4222 |
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+ | 0.0002 | 50.0 | 300 | 4.1726 | 0.4222 |
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  ### Framework versions
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