| | ---
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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-RX2-12
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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: 0.7391304347826086
|
| | ---
|
| |
|
| | <!-- 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. -->
|
| |
|
| | # vit-base-patch16-224-RX2-12
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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: 0.7887
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| | - Accuracy: 0.7391
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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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| |
|
| | ## 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: 12
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| |
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| | ### Training results
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| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| | | 1.3604 | 0.94 | 11 | 1.2834 | 0.4783 |
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| | | 1.2312 | 1.96 | 23 | 1.1356 | 0.6522 |
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| | | 1.0933 | 2.98 | 35 | 1.0386 | 0.6739 |
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| | | 0.936 | 4.0 | 47 | 0.9049 | 0.6739 |
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| | | 0.8011 | 4.94 | 58 | 0.9847 | 0.6087 |
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| | | 0.616 | 5.96 | 70 | 0.9236 | 0.6304 |
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| | | 0.5251 | 6.98 | 82 | 0.8640 | 0.6522 |
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| | | 0.4618 | 8.0 | 94 | 0.8612 | 0.7174 |
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| | | 0.3974 | 8.94 | 105 | 0.8461 | 0.6522 |
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| | | 0.3532 | 9.96 | 117 | 0.7887 | 0.7391 |
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| | | 0.335 | 10.98 | 129 | 0.7995 | 0.7174 |
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| | | 0.3211 | 11.23 | 132 | 0.8058 | 0.7174 |
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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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| |
|
