| | ---
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| | license: apache-2.0
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| | base_model: google/vit-base-patch16-224
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| | tags:
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| | - generated_from_trainer
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| | datasets:
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| | - imagefolder
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| | metrics:
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| | - accuracy
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| | model-index:
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| | - name: vit-base-patch16-224-R1-10
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| | results:
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| | - task:
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| | name: Image Classification
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| | type: image-classification
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| | dataset:
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| | name: imagefolder
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| | type: imagefolder
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| | config: default
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| | split: validation
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| | args: default
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| | metrics:
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| | - name: Accuracy
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| | type: accuracy
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| | value: 0.7049180327868853
|
| | ---
|
| |
|
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| | should probably proofread and complete it, then remove this comment. -->
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| |
|
| | # vit-base-patch16-224-R1-10
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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: 1.2451
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| | - Accuracy: 0.7049
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| |
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| | ## Model description
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| |
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| | More information needed
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| |
|
| | ## Intended uses & limitations
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| |
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| | More information needed
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| |
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| | ## Training and evaluation data
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| |
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| | More information needed
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| |
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| | ## Training procedure
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| |
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| | ### Training hyperparameters
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| |
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| | The following hyperparameters were used during training:
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| | - learning_rate: 5.5e-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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| | - gradient_accumulation_steps: 4
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| | - total_train_batch_size: 128
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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: 0.05
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| | - num_epochs: 10
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| |
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| | ### Training results
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| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| | | 1.1675 | 0.99 | 38 | 0.9972 | 0.6393 |
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| | | 0.5606 | 1.99 | 76 | 0.7603 | 0.6885 |
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| | | 0.3159 | 2.98 | 114 | 0.8954 | 0.6885 |
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| | | 0.2253 | 4.0 | 153 | 1.0227 | 0.6885 |
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| | | 0.17 | 4.99 | 191 | 1.1025 | 0.7213 |
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| | | 0.1174 | 5.99 | 229 | 1.1453 | 0.7377 |
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| | | 0.1032 | 6.98 | 267 | 1.0995 | 0.6885 |
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| | | 0.1051 | 8.0 | 306 | 1.2167 | 0.7049 |
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| | | 0.0853 | 8.99 | 344 | 1.2042 | 0.7377 |
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| | | 0.0802 | 9.93 | 380 | 1.2451 | 0.7049 |
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| |
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| |
|
| | ### Framework versions
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| |
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| | - Transformers 4.36.2
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| | - Pytorch 2.1.2+cu118
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| | - Datasets 2.16.1
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| | - Tokenizers 0.15.0
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| |
|
