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onizukal
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Boya3_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold4

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +9 -14
  2. pytorch_model.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: 0.8403960396039604
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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: 1.5511
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- - Accuracy: 0.8404
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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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- | 0.4103 | 1.0 | 632 | 0.4783 | 0.8048 |
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- | 0.2793 | 2.0 | 1264 | 0.4295 | 0.8222 |
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- | 0.2258 | 3.0 | 1896 | 0.4738 | 0.8238 |
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- | 0.063 | 4.0 | 2528 | 0.8564 | 0.84 |
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- | 0.0134 | 5.0 | 3160 | 1.0907 | 0.8388 |
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- | 0.0185 | 6.0 | 3792 | 1.3763 | 0.8396 |
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- | 0.0092 | 7.0 | 4424 | 1.4472 | 0.8380 |
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- | 0.0 | 8.0 | 5056 | 1.5323 | 0.8372 |
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- | 0.0 | 9.0 | 5688 | 1.5340 | 0.8404 |
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- | 0.0 | 10.0 | 6320 | 1.5511 | 0.8404 |
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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: 0.8348514851485148
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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: 1.0857
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+ - Accuracy: 0.8349
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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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+ | 0.3968 | 1.0 | 632 | 0.5064 | 0.7988 |
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+ | 0.2217 | 2.0 | 1264 | 0.4437 | 0.8210 |
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+ | 0.1633 | 3.0 | 1896 | 0.5150 | 0.8309 |
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+ | 0.0261 | 4.0 | 2528 | 0.9455 | 0.8352 |
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+ | 0.0033 | 5.0 | 3160 | 1.0857 | 0.8349 |
 
 
 
 
 
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  ### Framework versions
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