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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: urinary_carcinoma_classifier_g001 |
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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[:33] |
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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: 0.8571428571428571 |
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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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# urinary_carcinoma_classifier_g001 |
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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: 0.3828 |
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- Accuracy: 0.8571 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 30 |
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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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| No log | 1.0 | 1 | 0.6854 | 0.7143 | |
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| No log | 2.0 | 2 | 0.6759 | 0.5714 | |
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| No log | 3.0 | 3 | 0.6738 | 0.5714 | |
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| No log | 4.0 | 4 | 0.6571 | 0.5714 | |
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| No log | 5.0 | 5 | 0.6342 | 0.5714 | |
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| No log | 6.0 | 6 | 0.6339 | 0.5714 | |
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| No log | 7.0 | 7 | 0.5402 | 0.5714 | |
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| No log | 8.0 | 8 | 0.5827 | 0.5714 | |
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| No log | 9.0 | 9 | 0.5439 | 0.7143 | |
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| 0.2718 | 10.0 | 10 | 0.5553 | 0.7143 | |
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| 0.2718 | 11.0 | 11 | 0.4241 | 1.0 | |
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| 0.2718 | 12.0 | 12 | 0.5177 | 0.8571 | |
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| 0.2718 | 13.0 | 13 | 0.4088 | 0.8571 | |
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| 0.2718 | 14.0 | 14 | 0.4763 | 0.7143 | |
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| 0.2718 | 15.0 | 15 | 0.3164 | 1.0 | |
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| 0.2718 | 16.0 | 16 | 0.3087 | 1.0 | |
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| 0.2718 | 17.0 | 17 | 0.3457 | 0.8571 | |
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| 0.2718 | 18.0 | 18 | 0.2585 | 1.0 | |
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| 0.2718 | 19.0 | 19 | 0.3642 | 0.8571 | |
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| 0.1299 | 20.0 | 20 | 0.4421 | 0.7143 | |
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| 0.1299 | 21.0 | 21 | 0.3558 | 0.8571 | |
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| 0.1299 | 22.0 | 22 | 0.3611 | 0.8571 | |
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| 0.1299 | 23.0 | 23 | 0.5796 | 0.7143 | |
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| 0.1299 | 24.0 | 24 | 0.4137 | 0.8571 | |
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| 0.1299 | 25.0 | 25 | 0.4281 | 0.8571 | |
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| 0.1299 | 26.0 | 26 | 0.2066 | 1.0 | |
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| 0.1299 | 27.0 | 27 | 0.2251 | 1.0 | |
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| 0.1299 | 28.0 | 28 | 0.2459 | 1.0 | |
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| 0.1299 | 29.0 | 29 | 0.4450 | 0.8571 | |
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| 0.0743 | 30.0 | 30 | 0.3828 | 0.8571 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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