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onizukal
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Boya1_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold2

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: 0.8397297297297297
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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: 1.6549
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- - Accuracy: 0.8397
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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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- | 0.4334 | 1.0 | 923 | 0.4261 | 0.8314 |
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- | 0.3478 | 2.0 | 1846 | 0.4091 | 0.8357 |
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- | 0.2025 | 3.0 | 2769 | 0.6347 | 0.8408 |
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- | 0.0819 | 4.0 | 3692 | 0.8142 | 0.8341 |
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- | 0.1361 | 5.0 | 4615 | 1.0819 | 0.8441 |
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- | 0.0324 | 6.0 | 5538 | 1.3598 | 0.8427 |
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- | 0.0035 | 7.0 | 6461 | 1.6238 | 0.8430 |
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- | 0.0 | 8.0 | 7384 | 1.6312 | 0.8405 |
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- | 0.0002 | 9.0 | 8307 | 1.6680 | 0.8405 |
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- | 0.0001 | 10.0 | 9230 | 1.6549 | 0.8397 |
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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: 0.8421621621621621
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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: 1.0703
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+ - Accuracy: 0.8422
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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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+ | 0.4897 | 1.0 | 923 | 0.4183 | 0.8332 |
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+ | 0.3508 | 2.0 | 1846 | 0.4051 | 0.8403 |
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+ | 0.248 | 3.0 | 2769 | 0.6150 | 0.8459 |
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+ | 0.1818 | 4.0 | 3692 | 0.8410 | 0.8446 |
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+ | 0.0386 | 5.0 | 4615 | 1.0703 | 0.8422 |
 
 
 
 
 
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  ### Framework versions
pytorch_model.bin CHANGED
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