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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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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- f1 |
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model-index: |
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- name: vit-base-patch16-224-in21k |
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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: F1 |
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type: f1 |
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value: 0.960503161050642 |
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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-in21k |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0377 |
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- F1: 0.9605 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.1855 | 0.99 | 53 | 0.1819 | 0.4851 | |
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| 0.1147 | 1.99 | 107 | 0.1140 | 0.7505 | |
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| 0.1075 | 3.0 | 161 | 0.0932 | 0.8654 | |
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| 0.0755 | 4.0 | 215 | 0.0684 | 0.9268 | |
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| 0.0605 | 4.99 | 268 | 0.0584 | 0.9294 | |
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| 0.0475 | 5.99 | 322 | 0.0436 | 0.9550 | |
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| 0.0442 | 7.0 | 376 | 0.0503 | 0.9367 | |
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| 0.0464 | 8.0 | 430 | 0.0398 | 0.9599 | |
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| 0.0267 | 8.99 | 483 | 0.0445 | 0.9423 | |
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| 0.0374 | 9.86 | 530 | 0.0377 | 0.9605 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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