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onizukal
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Boya2_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold1

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: 0.8595336076817558
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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: 1.4832
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- - Accuracy: 0.8595
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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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- | 0.3205 | 1.0 | 914 | 0.4126 | 0.8335 |
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- | 0.3896 | 2.0 | 1828 | 0.3489 | 0.8595 |
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- | 0.2815 | 3.0 | 2742 | 0.4941 | 0.8250 |
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- | 0.0932 | 4.0 | 3656 | 0.8851 | 0.8431 |
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- | 0.0061 | 5.0 | 4570 | 1.0518 | 0.8527 |
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- | 0.0199 | 6.0 | 5484 | 1.2561 | 0.8529 |
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- | 0.0725 | 7.0 | 6398 | 1.4266 | 0.8565 |
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- | 0.0 | 8.0 | 7312 | 1.4824 | 0.8543 |
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- | 0.0 | 9.0 | 8226 | 1.4678 | 0.8579 |
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- | 0.0 | 10.0 | 9140 | 1.4832 | 0.8595 |
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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: 0.8499314128943759
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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: 1.0671
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+ - Accuracy: 0.8499
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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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+ | 0.3239 | 1.0 | 914 | 0.3581 | 0.8494 |
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+ | 0.371 | 2.0 | 1828 | 0.3282 | 0.8650 |
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+ | 0.2987 | 3.0 | 2742 | 0.4357 | 0.8494 |
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+ | 0.0465 | 4.0 | 3656 | 0.8207 | 0.8499 |
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+ | 0.0005 | 5.0 | 4570 | 1.0671 | 0.8499 |
 
 
 
 
 
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  ### Framework versions
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