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Dimasnoufal
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image_classification

Image Classification
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vit
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  1. README.md +18 -11
  2. model.safetensors +1 -1
  3. runs/Feb09_12-59-03_d4057315a0e6/events.out.tfevents.1707483556.d4057315a0e6.1062.5 +2 -2
  4. runs/Feb09_12-59-03_d4057315a0e6/events.out.tfevents.1707483944.d4057315a0e6.1062.6 +3 -0
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: 0.6125
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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: 1.1916
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- - Accuracy: 0.6125
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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: 5e-05
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- - train_batch_size: 24
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- - eval_batch_size: 24
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  - seed: 42
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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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- - num_epochs: 3
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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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- | No log | 1.0 | 30 | 1.2213 | 0.55 |
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- | No log | 2.0 | 60 | 1.3069 | 0.575 |
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- | No log | 3.0 | 90 | 1.1196 | 0.6125 |
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.16.1
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  - Tokenizers 0.15.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.675
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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: 1.0801
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+ - Accuracy: 0.675
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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: 6e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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  - seed: 42
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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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+ - 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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+ | No log | 1.0 | 23 | 1.0917 | 0.625 |
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+ | No log | 2.0 | 46 | 1.1605 | 0.6125 |
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+ | No log | 3.0 | 69 | 1.0543 | 0.6375 |
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+ | No log | 4.0 | 92 | 1.1663 | 0.6 |
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+ | No log | 5.0 | 115 | 1.2546 | 0.5875 |
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+ | No log | 6.0 | 138 | 1.0580 | 0.6 |
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+ | No log | 7.0 | 161 | 1.1193 | 0.6125 |
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+ | No log | 8.0 | 184 | 1.2297 | 0.525 |
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+ | No log | 9.0 | 207 | 1.2295 | 0.55 |
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+ | No log | 10.0 | 230 | 1.0842 | 0.6125 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.0
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  - Tokenizers 0.15.1
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