| ---
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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-RXL1-24
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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: 0.8431372549019608
|
| ---
|
|
|
| <!-- 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-RXL1-24
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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: 0.6158
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| - Accuracy: 0.8431
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|
|
| ## Model description
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|
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| More information needed
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|
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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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|
|
| ### 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: 24
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|
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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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| | 1.3745 | 0.95 | 13 | 1.3056 | 0.4706 |
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| | 1.2896 | 1.96 | 27 | 1.1039 | 0.6471 |
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| | 0.9896 | 2.98 | 41 | 0.9413 | 0.6471 |
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| | 0.8472 | 4.0 | 55 | 0.9059 | 0.6275 |
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| | 0.7375 | 4.95 | 68 | 0.6520 | 0.8039 |
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| | 0.458 | 5.96 | 82 | 0.6754 | 0.8039 |
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| | 0.3807 | 6.98 | 96 | 0.6158 | 0.8431 |
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| | 0.3003 | 8.0 | 110 | 0.5666 | 0.8039 |
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| | 0.2337 | 8.95 | 123 | 0.5409 | 0.8039 |
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| | 0.2252 | 9.96 | 137 | 0.7382 | 0.7647 |
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| | 0.1644 | 10.98 | 151 | 0.6363 | 0.8039 |
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| | 0.1608 | 12.0 | 165 | 0.6941 | 0.8039 |
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| | 0.1354 | 12.95 | 178 | 0.6985 | 0.7843 |
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| | 0.1298 | 13.96 | 192 | 0.6610 | 0.8039 |
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| | 0.1333 | 14.98 | 206 | 0.6751 | 0.8039 |
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| | 0.1209 | 16.0 | 220 | 0.7723 | 0.7843 |
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| | 0.1057 | 16.95 | 233 | 0.8038 | 0.7255 |
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| | 0.0972 | 17.96 | 247 | 0.8375 | 0.7647 |
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| | 0.0789 | 18.98 | 261 | 0.6971 | 0.8235 |
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| | 0.0833 | 20.0 | 275 | 0.7507 | 0.7843 |
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| | 0.0813 | 20.95 | 288 | 0.7085 | 0.7843 |
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| | 0.0803 | 21.96 | 302 | 0.7566 | 0.7647 |
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| | 0.0693 | 22.69 | 312 | 0.7772 | 0.7647 |
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| ### Framework versions
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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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|
|
