| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - medmnist-v2 |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: ViT_breastmnist_std_60 |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: medmnist-v2 |
| | type: medmnist-v2 |
| | config: breastmnist |
| | split: validation |
| | args: breastmnist |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.7756410256410257 |
| | - name: F1 |
| | type: f1 |
| | value: 0.6137247966041741 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # ViT_breastmnist_std_60 |
| | |
| | This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the medmnist-v2 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5157 |
| | - Accuracy: 0.7756 |
| | - F1: 0.6137 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 2e-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | | 0.5179 | 0.2597 | 20 | 0.5240 | 0.7436 | 0.5385 | |
| | | 0.4306 | 0.5195 | 40 | 0.4807 | 0.7949 | 0.6855 | |
| | | 0.4258 | 0.7792 | 60 | 0.4812 | 0.7949 | 0.6518 | |
| | | 0.4613 | 1.0390 | 80 | 0.4491 | 0.8333 | 0.7247 | |
| | | 0.4194 | 1.2987 | 100 | 0.4573 | 0.8333 | 0.7247 | |
| | | 0.3693 | 1.5584 | 120 | 0.4665 | 0.8205 | 0.6953 | |
| | | 0.3825 | 1.8182 | 140 | 0.4695 | 0.7821 | 0.6733 | |
| | | 0.387 | 2.0779 | 160 | 0.4410 | 0.8205 | 0.7248 | |
| | | 0.3341 | 2.3377 | 180 | 0.4422 | 0.8205 | 0.7367 | |
| | | 0.3192 | 2.5974 | 200 | 0.4457 | 0.8205 | 0.7111 | |
| | | 0.3062 | 2.8571 | 220 | 0.4575 | 0.8205 | 0.7111 | |
| | | 0.2485 | 3.1169 | 240 | 0.4526 | 0.8333 | 0.7383 | |
| | | 0.2415 | 3.3766 | 260 | 0.4430 | 0.8462 | 0.7641 | |
| | | 0.2377 | 3.6364 | 280 | 0.4529 | 0.8333 | 0.7247 | |
| | | 0.2417 | 3.8961 | 300 | 0.4386 | 0.8205 | 0.7111 | |
| | | 0.1783 | 4.1558 | 320 | 0.4467 | 0.8333 | 0.7383 | |
| | | 0.193 | 4.4156 | 340 | 0.4724 | 0.8077 | 0.6823 | |
| | | 0.1736 | 4.6753 | 360 | 0.4757 | 0.8333 | 0.7383 | |
| | | 0.1656 | 4.9351 | 380 | 0.4677 | 0.8333 | 0.7383 | |
| | | 0.1214 | 5.1948 | 400 | 0.4747 | 0.8077 | 0.6981 | |
| | | 0.0851 | 5.4545 | 420 | 0.4782 | 0.7949 | 0.6698 | |
| | | 0.0893 | 5.7143 | 440 | 0.4842 | 0.8077 | 0.6823 | |
| | | 0.0978 | 5.9740 | 460 | 0.4883 | 0.8077 | 0.6823 | |
| | | 0.0518 | 6.2338 | 480 | 0.4861 | 0.8077 | 0.6981 | |
| | | 0.0662 | 6.4935 | 500 | 0.5017 | 0.8077 | 0.6981 | |
| | | 0.058 | 6.7532 | 520 | 0.5092 | 0.7949 | 0.6518 | |
| | | 0.0511 | 7.0130 | 540 | 0.5003 | 0.8205 | 0.7111 | |
| | | 0.0235 | 7.2727 | 560 | 0.5041 | 0.8077 | 0.6823 | |
| | | 0.0204 | 7.5325 | 580 | 0.5140 | 0.8205 | 0.7111 | |
| | | 0.0196 | 7.7922 | 600 | 0.5122 | 0.8205 | 0.7111 | |
| | | 0.0108 | 8.0519 | 620 | 0.5186 | 0.8205 | 0.7111 | |
| | | 0.012 | 8.3117 | 640 | 0.5315 | 0.8333 | 0.7247 | |
| | | 0.0077 | 8.5714 | 660 | 0.5319 | 0.8205 | 0.7111 | |
| | | 0.0187 | 8.8312 | 680 | 0.5279 | 0.8205 | 0.7111 | |
| | | 0.0063 | 9.0909 | 700 | 0.5304 | 0.8205 | 0.7111 | |
| | | 0.004 | 9.3506 | 720 | 0.5312 | 0.8205 | 0.7111 | |
| | | 0.0044 | 9.6104 | 740 | 0.5310 | 0.8205 | 0.7111 | |
| | | 0.0076 | 9.8701 | 760 | 0.5323 | 0.8205 | 0.7111 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.45.1 |
| | - Pytorch 2.4.0 |
| | - Datasets 3.0.1 |
| | - Tokenizers 0.20.0 |
| | |
