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---
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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-ve-U13b-80RX3
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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: 0.9130434782608695
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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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should probably proofread and complete it, then remove this comment. -->
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# vit-base-patch16-224-ve-U13b-80RX3
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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: 0.4344
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- Accuracy: 0.9130
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4.74e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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: 40
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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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| 1.33 | 0.99 | 51 | 1.3133 | 0.3478 |
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| 1.0288 | 2.0 | 103 | 1.0045 | 0.5652 |
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| 0.7322 | 2.99 | 154 | 0.7309 | 0.8043 |
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| 0.5476 | 4.0 | 206 | 0.6316 | 0.7826 |
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| 0.2863 | 4.99 | 257 | 0.5598 | 0.8043 |
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| 0.3149 | 6.0 | 309 | 0.5428 | 0.8478 |
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| 0.1489 | 6.99 | 360 | 0.5150 | 0.8696 |
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| 0.1134 | 8.0 | 412 | 0.4585 | 0.8043 |
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| 0.1613 | 8.99 | 463 | 0.6284 | 0.8478 |
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| 0.1855 | 10.0 | 515 | 0.5985 | 0.8478 |
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| 0.1908 | 10.99 | 566 | 1.0336 | 0.7391 |
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| 0.2293 | 12.0 | 618 | 0.7746 | 0.8043 |
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| 0.1414 | 12.99 | 669 | 0.6517 | 0.8261 |
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| 0.0877 | 14.0 | 721 | 0.5639 | 0.8261 |
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| 0.1302 | 14.99 | 772 | 0.7687 | 0.8261 |
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| 0.047 | 16.0 | 824 | 0.6773 | 0.8696 |
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| 0.1045 | 16.99 | 875 | 0.4344 | 0.9130 |
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| 0.0751 | 18.0 | 927 | 1.0160 | 0.7391 |
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| 0.1141 | 18.99 | 978 | 0.6643 | 0.8696 |
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| 0.1756 | 20.0 | 1030 | 0.5582 | 0.8913 |
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| 0.1212 | 20.99 | 1081 | 0.5641 | 0.8913 |
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| 0.0903 | 22.0 | 1133 | 0.6990 | 0.8261 |
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| 0.0693 | 22.99 | 1184 | 0.5548 | 0.8913 |
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| 0.0048 | 24.0 | 1236 | 0.6958 | 0.8478 |
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| 0.0785 | 24.99 | 1287 | 0.7886 | 0.8043 |
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| 0.0373 | 26.0 | 1339 | 0.6345 | 0.8478 |
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| 0.0763 | 26.99 | 1390 | 0.6830 | 0.8696 |
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| 0.0621 | 28.0 | 1442 | 0.7294 | 0.8478 |
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| 0.0367 | 28.99 | 1493 | 0.6636 | 0.8696 |
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| 0.0124 | 30.0 | 1545 | 0.8031 | 0.8478 |
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| 0.0759 | 30.99 | 1596 | 0.7076 | 0.8696 |
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| 0.0786 | 32.0 | 1648 | 0.8024 | 0.8261 |
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| 0.0487 | 32.99 | 1699 | 0.7927 | 0.8696 |
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| 0.0664 | 34.0 | 1751 | 0.9607 | 0.8261 |
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| 0.0054 | 34.99 | 1802 | 0.9702 | 0.8261 |
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| 0.0277 | 36.0 | 1854 | 0.8351 | 0.8261 |
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| 0.0025 | 36.99 | 1905 | 0.9318 | 0.8261 |
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| 0.0188 | 38.0 | 1957 | 0.8995 | 0.8478 |
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| 0.0385 | 38.99 | 2008 | 0.8928 | 0.8478 |
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| 0.0474 | 39.61 | 2040 | 0.8863 | 0.8478 |
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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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