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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-finalterm |
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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: 0.88125 |
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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-finalterm |
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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: 0.3547 |
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- Accuracy: 0.8812 |
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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: 15 |
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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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| 1.3999 | 1.0 | 10 | 1.1607 | 0.5094 | |
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| 0.993 | 2.0 | 20 | 0.7807 | 0.7031 | |
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| 0.6819 | 3.0 | 30 | 0.5753 | 0.8063 | |
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| 0.5485 | 4.0 | 40 | 0.6475 | 0.7594 | |
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| 0.463 | 5.0 | 50 | 0.4393 | 0.8406 | |
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| 0.3929 | 6.0 | 60 | 0.4067 | 0.8625 | |
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| 0.3636 | 7.0 | 70 | 0.3626 | 0.8875 | |
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| 0.3719 | 8.0 | 80 | 0.3613 | 0.8875 | |
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| 0.343 | 9.0 | 90 | 0.3624 | 0.8781 | |
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| 0.3297 | 10.0 | 100 | 0.3800 | 0.8625 | |
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| 0.2948 | 11.0 | 110 | 0.3320 | 0.8938 | |
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| 0.33 | 12.0 | 120 | 0.3481 | 0.8781 | |
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| 0.3281 | 13.0 | 130 | 0.3418 | 0.8875 | |
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| 0.3 | 14.0 | 140 | 0.3425 | 0.8844 | |
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| 0.3014 | 15.0 | 150 | 0.3547 | 0.8812 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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