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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 +16 -16
  2. model.safetensors +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: 0.7423708920187794
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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
@@ -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: 0.7556
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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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  | 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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- - Transformers 4.34.1
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  - Pytorch 2.1.0+cu118
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- - Datasets 2.14.5
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  - Tokenizers 0.14.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7570422535211268
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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: 0.6881
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+ - Accuracy: 0.7570
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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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+ | 1.3494 | 1.0 | 62 | 1.1001 | 0.6350 |
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+ | 0.9612 | 1.99 | 124 | 0.8708 | 0.6772 |
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+ | 0.8817 | 2.99 | 186 | 0.7898 | 0.7265 |
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+ | 0.8362 | 4.0 | 249 | 0.7643 | 0.7277 |
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+ | 0.7959 | 5.0 | 311 | 0.7310 | 0.7383 |
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+ | 0.6765 | 5.99 | 373 | 0.7247 | 0.7471 |
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+ | 0.6504 | 6.99 | 435 | 0.6939 | 0.7576 |
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+ | 0.5846 | 8.0 | 498 | 0.6983 | 0.7576 |
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+ | 0.5774 | 9.0 | 560 | 0.6935 | 0.7594 |
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+ | 0.5749 | 9.96 | 620 | 0.6881 | 0.7570 |
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  ### Framework versions
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+ - Transformers 4.35.0
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  - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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  - Tokenizers 0.14.1
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