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HorcruxNo13
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beit-base-patch16-224-pt22k-ft22k

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results (legacy)
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  1. README.md +7 -7
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: 0.725
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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-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6314
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- - Accuracy: 0.725
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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: 0.05
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 8 | 2.4704 | 0.275 |
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- | 8.3532 | 2.0 | 16 | 0.6854 | 0.725 |
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- | 0.9363 | 3.0 | 24 | 0.6314 | 0.725 |
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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: 0.6866666666666666
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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-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6312
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+ - Accuracy: 0.6867
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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: 32
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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 | 8 | 3.4268 | 0.275 |
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+ | 6.7921 | 2.0 | 16 | 0.6216 | 0.7083 |
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+ | 0.7831 | 3.0 | 24 | 0.5972 | 0.7417 |
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  ### Framework versions