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ihsansatriawan
/
image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Model card Files Community
2
ihsansatriawan commited on
Commit
ef9d992
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1 Parent(s): bd9f559

End of training

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Files changed (3) hide show
  1. README.md +7 -7
  2. pytorch_model.bin +2 -2
  3. training_args.bin +2 -2
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: 0.4125
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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: 1.7875
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- - Accuracy: 0.4125
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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: 32
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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 | 20 | 1.9763 | 0.325 |
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- | No log | 2.0 | 40 | 1.8310 | 0.4062 |
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- | No log | 3.0 | 60 | 1.7842 | 0.425 |
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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: 0.45625
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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: 1.4732
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+ - Accuracy: 0.4562
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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: 8e-05
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  - train_batch_size: 32
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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 | 20 | 1.5536 | 0.475 |
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+ | No log | 2.0 | 40 | 1.4331 | 0.5375 |
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+ | No log | 3.0 | 60 | 1.4045 | 0.5188 |
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  ### Framework versions
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