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End of training

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  1. README.md +9 -14
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@@ -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: 0.8299723210755239
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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/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6702
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- - Accuracy: 0.8300
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  ## Model description
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@@ -59,22 +59,17 @@ 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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- | 0.4648 | 1.0 | 632 | 0.4488 | 0.8043 |
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- | 0.3305 | 2.0 | 1264 | 0.4801 | 0.8300 |
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- | 0.2644 | 3.0 | 1896 | 0.4984 | 0.8173 |
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- | 0.0426 | 4.0 | 2528 | 0.9639 | 0.8327 |
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- | 0.0408 | 5.0 | 3160 | 1.2519 | 0.8383 |
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- | 0.0134 | 6.0 | 3792 | 1.4345 | 0.8319 |
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- | 0.0 | 7.0 | 4424 | 1.5640 | 0.8327 |
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- | 0.0001 | 8.0 | 5056 | 1.6117 | 0.8343 |
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- | 0.0 | 9.0 | 5688 | 1.6490 | 0.8319 |
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- | 0.0 | 10.0 | 6320 | 1.6702 | 0.8300 |
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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: 0.8382759984183472
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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/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1301
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+ - Accuracy: 0.8383
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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: 5
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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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+ | 0.48 | 1.0 | 632 | 0.4558 | 0.8106 |
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+ | 0.3393 | 2.0 | 1264 | 0.4738 | 0.8312 |
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+ | 0.3238 | 3.0 | 1896 | 0.5381 | 0.8375 |
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+ | 0.0626 | 4.0 | 2528 | 0.9352 | 0.8359 |
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+ | 0.0011 | 5.0 | 3160 | 1.1301 | 0.8383 |
 
 
 
 
 
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  ### Framework versions