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WillyArdiyanto
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image_classification

Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +14 -14
README.md CHANGED
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.46875
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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5007
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- - Accuracy: 0.4688
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 40 | 1.6852 | 0.375 |
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- | No log | 2.0 | 80 | 1.6358 | 0.3875 |
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- | No log | 3.0 | 120 | 1.5966 | 0.4313 |
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- | No log | 4.0 | 160 | 1.5847 | 0.4125 |
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- | No log | 5.0 | 200 | 1.5257 | 0.5 |
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- | No log | 6.0 | 240 | 1.5191 | 0.475 |
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- | No log | 7.0 | 280 | 1.5078 | 0.4562 |
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- | No log | 8.0 | 320 | 1.4900 | 0.5125 |
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- | No log | 9.0 | 360 | 1.5175 | 0.4437 |
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- | No log | 10.0 | 400 | 1.4984 | 0.4813 |
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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: 0.5625
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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4866
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+ - Accuracy: 0.5625
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 40 | 1.5045 | 0.4875 |
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+ | No log | 2.0 | 80 | 1.3562 | 0.5312 |
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+ | No log | 3.0 | 120 | 1.5354 | 0.4562 |
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+ | No log | 4.0 | 160 | 1.5095 | 0.5062 |
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+ | No log | 5.0 | 200 | 1.5644 | 0.475 |
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+ | No log | 6.0 | 240 | 1.4651 | 0.5563 |
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+ | No log | 7.0 | 280 | 1.4516 | 0.5375 |
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+ | No log | 8.0 | 320 | 1.5859 | 0.5188 |
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+ | No log | 9.0 | 360 | 1.5498 | 0.5437 |
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+ | No log | 10.0 | 400 | 1.5040 | 0.5625 |
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  ### Framework versions