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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-pure-ViT |
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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: train |
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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: 0.8714733542319749 |
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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-pure-ViT |
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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: 0.3270 |
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- Accuracy: 0.8715 |
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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: 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: 0.1 |
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- num_epochs: 10 |
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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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| 0.4676 | 1.0 | 202 | 0.4042 | 0.8095 | |
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| 0.4605 | 2.0 | 404 | 0.3675 | 0.8377 | |
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| 0.4012 | 3.0 | 606 | 0.3486 | 0.8506 | |
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| 0.3727 | 4.0 | 808 | 0.3413 | 0.8481 | |
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| 0.3482 | 5.0 | 1010 | 0.3339 | 0.8614 | |
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| 0.354 | 6.0 | 1212 | 0.3436 | 0.8561 | |
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| 0.3212 | 7.0 | 1414 | 0.3415 | 0.8534 | |
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| 0.3263 | 8.0 | 1616 | 0.3281 | 0.8642 | |
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| 0.285 | 9.0 | 1818 | 0.3263 | 0.8673 | |
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| 0.2779 | 10.0 | 2020 | 0.3270 | 0.8715 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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