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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: cards-vit-base-patch16-224-finetuned-v1 |
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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: test |
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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: 0.31704202872849796 |
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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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# cards-vit-base-patch16-224-finetuned-v1 |
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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: 1.9972 |
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- Accuracy: 0.3170 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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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| 1.7068 | 0.9993 | 378 | 1.9533 | 0.2753 | |
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| 1.6691 | 1.9987 | 756 | 1.9642 | 0.2864 | |
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| 1.6278 | 2.9980 | 1134 | 1.9935 | 0.3018 | |
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| 1.5837 | 4.0 | 1513 | 2.0155 | 0.3077 | |
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| 1.5263 | 4.9993 | 1891 | 2.0283 | 0.3063 | |
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| 1.4969 | 5.9987 | 2269 | 2.0026 | 0.3081 | |
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| 1.5088 | 6.9980 | 2647 | 2.0275 | 0.3098 | |
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| 1.4623 | 8.0 | 3026 | 2.0096 | 0.3137 | |
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| 1.4305 | 8.9993 | 3404 | 2.0239 | 0.3154 | |
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| 1.3895 | 9.9934 | 3780 | 1.9972 | 0.3170 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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