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deit-tiny-patch16-224-finetuned-papsmear

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  1. README.md +18 -18
  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: 0.8529411764705882
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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: 0.4389
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- - Accuracy: 0.8529
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  ## Model description
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@@ -67,21 +67,21 @@ 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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- | 1.8247 | 0.9870 | 19 | 1.6199 | 0.3015 |
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- | 1.415 | 1.9740 | 38 | 1.2594 | 0.5147 |
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- | 1.06 | 2.9610 | 57 | 1.0316 | 0.6471 |
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- | 0.8808 | 4.0 | 77 | 1.0088 | 0.625 |
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- | 0.7646 | 4.9870 | 96 | 0.8211 | 0.6985 |
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- | 0.6798 | 5.9740 | 115 | 0.7383 | 0.7132 |
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- | 0.554 | 6.9610 | 134 | 0.6477 | 0.7574 |
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- | 0.5358 | 8.0 | 154 | 0.5824 | 0.7647 |
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- | 0.4689 | 8.9870 | 173 | 0.5571 | 0.7794 |
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- | 0.4217 | 9.9740 | 192 | 0.5506 | 0.7868 |
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- | 0.4063 | 10.9610 | 211 | 0.4987 | 0.8235 |
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- | 0.3827 | 12.0 | 231 | 0.4793 | 0.8088 |
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- | 0.3095 | 12.9870 | 250 | 0.4724 | 0.8015 |
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- | 0.3521 | 13.9740 | 269 | 0.4389 | 0.8529 |
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- | 0.3397 | 14.8052 | 285 | 0.4383 | 0.8456 |
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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: 0.9117647058823529
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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: 0.3409
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+ - Accuracy: 0.9118
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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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+ | 0.3521 | 0.9870 | 19 | 0.4595 | 0.8235 |
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+ | 0.335 | 1.9740 | 38 | 0.4491 | 0.8603 |
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+ | 0.3248 | 2.9610 | 57 | 0.4196 | 0.875 |
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+ | 0.3271 | 4.0 | 77 | 0.5467 | 0.8015 |
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+ | 0.3286 | 4.9870 | 96 | 0.4768 | 0.8162 |
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+ | 0.2854 | 5.9740 | 115 | 0.4147 | 0.8676 |
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+ | 0.2291 | 6.9610 | 134 | 0.4321 | 0.8676 |
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+ | 0.2619 | 8.0 | 154 | 0.5726 | 0.8235 |
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+ | 0.2196 | 8.9870 | 173 | 0.4344 | 0.8676 |
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+ | 0.2116 | 9.9740 | 192 | 0.3809 | 0.875 |
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+ | 0.1913 | 10.9610 | 211 | 0.3757 | 0.8603 |
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+ | 0.1604 | 12.0 | 231 | 0.3551 | 0.8897 |
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+ | 0.1307 | 12.9870 | 250 | 0.3330 | 0.8971 |
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+ | 0.1425 | 13.9740 | 269 | 0.3421 | 0.9118 |
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+ | 0.141 | 14.8052 | 285 | 0.3409 | 0.9118 |
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  ### Framework versions
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