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onizukal
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Boya1_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold5

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: 0.8383509628424193
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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: 1.7570
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- - Accuracy: 0.8384
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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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- | 0.4796 | 1.0 | 924 | 0.4853 | 0.7977 |
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- | 0.3944 | 2.0 | 1848 | 0.4147 | 0.8394 |
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- | 0.1452 | 3.0 | 2772 | 0.5922 | 0.8327 |
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- | 0.062 | 4.0 | 3696 | 0.8561 | 0.8308 |
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- | 0.0098 | 5.0 | 4620 | 1.3565 | 0.8302 |
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- | 0.0354 | 6.0 | 5544 | 1.3887 | 0.8261 |
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- | 0.0001 | 7.0 | 6468 | 1.6246 | 0.8313 |
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- | 0.0002 | 8.0 | 7392 | 1.6532 | 0.8359 |
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- | 0.0 | 9.0 | 8316 | 1.7460 | 0.8362 |
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- | 0.0 | 10.0 | 9240 | 1.7570 | 0.8384 |
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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: 0.8378085164090046
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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: 1.2266
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+ - Accuracy: 0.8378
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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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+ | 0.5165 | 1.0 | 924 | 0.5083 | 0.7933 |
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+ | 0.3886 | 2.0 | 1848 | 0.4181 | 0.8378 |
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+ | 0.1118 | 3.0 | 2772 | 0.6643 | 0.8367 |
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+ | 0.0211 | 4.0 | 3696 | 0.9770 | 0.8402 |
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+ | 0.0006 | 5.0 | 4620 | 1.2266 | 0.8378 |
 
 
 
 
 
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  ### Framework versions
pytorch_model.bin CHANGED
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