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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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- accuracy |
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model-index: |
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- name: xyz |
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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: 0.9101851851851852 |
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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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# xyz |
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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: 0.3224 |
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- Accuracy: 0.9102 |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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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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| 1.2269 | 0.37 | 100 | 1.2058 | 0.6019 | |
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| 1.0891 | 0.74 | 200 | 0.9254 | 0.7046 | |
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| 0.5328 | 1.11 | 300 | 0.7417 | 0.7741 | |
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| 0.5259 | 1.48 | 400 | 0.7145 | 0.7722 | |
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| 0.4889 | 1.85 | 500 | 0.5621 | 0.825 | |
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| 0.2753 | 2.22 | 600 | 0.5251 | 0.8444 | |
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| 0.2569 | 2.59 | 700 | 0.5792 | 0.8259 | |
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| 0.2251 | 2.96 | 800 | 0.4169 | 0.8731 | |
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| 0.086 | 3.33 | 900 | 0.4182 | 0.8843 | |
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| 0.1352 | 3.7 | 1000 | 0.3711 | 0.8880 | |
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| 0.0608 | 4.07 | 1100 | 0.3430 | 0.9046 | |
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| 0.0175 | 4.44 | 1200 | 0.3241 | 0.9185 | |
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| 0.0149 | 4.81 | 1300 | 0.3224 | 0.9102 | |
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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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