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vit-base-patch16-224-type

Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
Metrics Community
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  1. README.md +15 -11
  2. pytorch_model.bin +1 -1
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: 0.7335680751173709
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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](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7623
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- - Accuracy: 0.7336
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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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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- | 1.1891 | 1.0 | 62 | 1.0237 | 0.6549 |
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- | 0.9452 | 1.99 | 124 | 0.8808 | 0.6948 |
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- | 0.8955 | 2.99 | 186 | 0.8164 | 0.7124 |
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- | 0.8389 | 4.0 | 249 | 0.7755 | 0.7283 |
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- | 0.8038 | 5.0 | 311 | 0.7651 | 0.7306 |
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- | 0.71 | 5.98 | 372 | 0.7623 | 0.7336 |
 
 
 
 
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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: 0.7423708920187794
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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](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7556
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+ - Accuracy: 0.7424
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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: 3e-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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  - lr_scheduler_warmup_ratio: 0.1
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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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+ | 0.5461 | 1.0 | 62 | 0.7743 | 0.7230 |
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+ | 0.4924 | 1.99 | 124 | 0.7858 | 0.7248 |
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+ | 0.5121 | 2.99 | 186 | 0.7973 | 0.7330 |
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+ | 0.5216 | 4.0 | 249 | 0.7749 | 0.7289 |
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+ | 0.5788 | 5.0 | 311 | 0.7801 | 0.7312 |
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+ | 0.5863 | 5.99 | 373 | 0.7705 | 0.7424 |
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+ | 0.5862 | 6.99 | 435 | 0.7560 | 0.7424 |
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+ | 0.5327 | 8.0 | 498 | 0.7631 | 0.7365 |
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+ | 0.5155 | 9.0 | 560 | 0.7560 | 0.7406 |
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+ | 0.511 | 9.96 | 620 | 0.7556 | 0.7424 |
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  ### Framework versions
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