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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_g002 |
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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[:63] |
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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: 0.9230769230769231 |
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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_g002 |
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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: 0.3544 |
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- Accuracy: 0.9231 |
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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 | 0.6814 | 0.5385 | |
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| No log | 2.0 | 2 | 0.6743 | 0.6923 | |
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| No log | 3.0 | 3 | 0.6449 | 0.7692 | |
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| No log | 4.0 | 4 | 0.6149 | 0.7692 | |
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| No log | 5.0 | 5 | 0.5980 | 0.7692 | |
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| No log | 6.0 | 6 | 0.5855 | 0.7692 | |
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| No log | 7.0 | 7 | 0.5663 | 0.7692 | |
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| No log | 8.0 | 8 | 0.5675 | 0.7692 | |
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| No log | 9.0 | 9 | 0.5530 | 0.7692 | |
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| 0.637 | 10.0 | 10 | 0.5246 | 0.8462 | |
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| 0.637 | 11.0 | 11 | 0.5135 | 0.7692 | |
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| 0.637 | 12.0 | 12 | 0.5296 | 0.8462 | |
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| 0.637 | 13.0 | 13 | 0.5340 | 0.8462 | |
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| 0.637 | 14.0 | 14 | 0.4781 | 0.9231 | |
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| 0.637 | 15.0 | 15 | 0.4870 | 0.8462 | |
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| 0.637 | 16.0 | 16 | 0.4701 | 0.8462 | |
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| 0.637 | 17.0 | 17 | 0.4521 | 1.0 | |
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| 0.637 | 18.0 | 18 | 0.4266 | 0.9231 | |
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| 0.637 | 19.0 | 19 | 0.4220 | 0.9231 | |
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| 0.4474 | 20.0 | 20 | 0.3837 | 0.9231 | |
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| 0.4474 | 21.0 | 21 | 0.4257 | 0.8462 | |
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| 0.4474 | 22.0 | 22 | 0.4093 | 0.9231 | |
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| 0.4474 | 23.0 | 23 | 0.4019 | 1.0 | |
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| 0.4474 | 24.0 | 24 | 0.4578 | 0.8462 | |
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| 0.4474 | 25.0 | 25 | 0.3932 | 1.0 | |
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| 0.4474 | 26.0 | 26 | 0.3838 | 1.0 | |
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| 0.4474 | 27.0 | 27 | 0.3627 | 1.0 | |
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| 0.4474 | 28.0 | 28 | 0.3862 | 0.9231 | |
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| 0.4474 | 29.0 | 29 | 0.3624 | 0.9231 | |
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| 0.3102 | 30.0 | 30 | 0.3544 | 0.9231 | |
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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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