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image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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ihsansatriawan commited on
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End of training

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Files changed (4) hide show
  1. README.md +39 -14
  2. config.json +1 -1
  3. pytorch_model.bin +2 -2
  4. training_args.bin +2 -2
README.md CHANGED
@@ -1,5 +1,6 @@
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -21,7 +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: 0.1375
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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
@@ -31,8 +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: 2.0892
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- - Accuracy: 0.1375
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  ## Model description
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@@ -51,29 +52,53 @@ More information needed
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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: 16
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  - eval_batch_size: 16
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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: 6
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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 | 40 | 2.0892 | 0.1375 |
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- | No log | 2.0 | 80 | 2.0891 | 0.1375 |
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- | No log | 3.0 | 120 | 2.0887 | 0.1375 |
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- | No log | 4.0 | 160 | 2.0887 | 0.1375 |
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- | No log | 5.0 | 200 | 2.0885 | 0.1375 |
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- | No log | 6.0 | 240 | 2.0885 | 0.1375 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.29.0
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- - Pytorch 2.0.1
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- - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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  ---
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  license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.16875
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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: 2.0822
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+ - Accuracy: 0.1688
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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: 0.02
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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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  - 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: 30
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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 | 40 | 2.1729 | 0.1187 |
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+ | No log | 2.0 | 80 | 2.1526 | 0.0813 |
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+ | No log | 3.0 | 120 | 2.1301 | 0.0813 |
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+ | No log | 4.0 | 160 | 2.1663 | 0.1313 |
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+ | No log | 5.0 | 200 | 2.1524 | 0.0813 |
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+ | No log | 6.0 | 240 | 2.0822 | 0.1688 |
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+ | No log | 7.0 | 280 | 2.1661 | 0.1187 |
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+ | No log | 8.0 | 320 | 2.1294 | 0.1375 |
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+ | No log | 9.0 | 360 | 2.0832 | 0.1562 |
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+ | No log | 10.0 | 400 | 2.1144 | 0.1187 |
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+ | No log | 11.0 | 440 | 2.1037 | 0.1187 |
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+ | No log | 12.0 | 480 | 2.1001 | 0.1562 |
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+ | 2.1281 | 13.0 | 520 | 2.1115 | 0.0813 |
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+ | 2.1281 | 14.0 | 560 | 2.0788 | 0.1187 |
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+ | 2.1281 | 15.0 | 600 | 2.1156 | 0.0813 |
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+ | 2.1281 | 16.0 | 640 | 2.1254 | 0.0813 |
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+ | 2.1281 | 17.0 | 680 | 2.0847 | 0.1688 |
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+ | 2.1281 | 18.0 | 720 | 2.0966 | 0.0813 |
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+ | 2.1281 | 19.0 | 760 | 2.1371 | 0.0813 |
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+ | 2.1281 | 20.0 | 800 | 2.0953 | 0.0813 |
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+ | 2.1281 | 21.0 | 840 | 2.0928 | 0.0875 |
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+ | 2.1281 | 22.0 | 880 | 2.1005 | 0.0813 |
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+ | 2.1281 | 23.0 | 920 | 2.0875 | 0.0875 |
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+ | 2.1281 | 24.0 | 960 | 2.0953 | 0.0813 |
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+ | 2.0868 | 25.0 | 1000 | 2.0931 | 0.0875 |
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+ | 2.0868 | 26.0 | 1040 | 2.0941 | 0.0875 |
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+ | 2.0868 | 27.0 | 1080 | 2.0949 | 0.0813 |
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+ | 2.0868 | 28.0 | 1120 | 2.0938 | 0.0875 |
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+ | 2.0868 | 29.0 | 1160 | 2.0940 | 0.0813 |
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+ | 2.0868 | 30.0 | 1200 | 2.0938 | 0.0875 |
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  ### Framework versions
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+ - Transformers 4.33.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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  - Tokenizers 0.13.3
config.json CHANGED
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  "problem_type": "single_label_classification",
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  "qkv_bias": true,
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  "torch_dtype": "float32",
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- "transformers_version": "4.29.0"
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  }
 
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  "problem_type": "single_label_classification",
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  "qkv_bias": true,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.33.2"
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  }
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