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--- |
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library_name: transformers |
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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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- medmnist-v2 |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: ViT_breastmnist_std_0 |
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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: medmnist-v2 |
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type: medmnist-v2 |
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config: breastmnist |
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split: validation |
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args: breastmnist |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8717948717948718 |
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- name: F1 |
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type: f1 |
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value: 0.8370927318295739 |
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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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# ViT_breastmnist_std_0 |
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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 medmnist-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3272 |
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- Accuracy: 0.8718 |
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- F1: 0.8371 |
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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: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 0.3533 | 0.2597 | 20 | 0.3035 | 0.8846 | 0.8406 | |
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| 0.1354 | 0.5195 | 40 | 0.2280 | 0.8974 | 0.8655 | |
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| 0.0247 | 0.7792 | 60 | 0.2669 | 0.9231 | 0.8956 | |
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| 0.0089 | 1.0390 | 80 | 0.2742 | 0.9231 | 0.8956 | |
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| 0.003 | 1.2987 | 100 | 0.3404 | 0.9103 | 0.8803 | |
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| 0.0018 | 1.5584 | 120 | 0.3583 | 0.9231 | 0.8956 | |
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| 0.0013 | 1.8182 | 140 | 0.3720 | 0.9231 | 0.8956 | |
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| 0.0009 | 2.0779 | 160 | 0.3892 | 0.9231 | 0.8956 | |
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| 0.0007 | 2.3377 | 180 | 0.3933 | 0.9231 | 0.8956 | |
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| 0.0006 | 2.5974 | 200 | 0.3948 | 0.9231 | 0.8956 | |
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| 0.0005 | 2.8571 | 220 | 0.4038 | 0.9231 | 0.8956 | |
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| 0.0005 | 3.1169 | 240 | 0.4145 | 0.9231 | 0.8956 | |
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| 0.0004 | 3.3766 | 260 | 0.4176 | 0.9231 | 0.8956 | |
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| 0.0004 | 3.6364 | 280 | 0.4230 | 0.9231 | 0.8956 | |
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| 0.0003 | 3.8961 | 300 | 0.4274 | 0.9103 | 0.8803 | |
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| 0.0003 | 4.1558 | 320 | 0.4344 | 0.9231 | 0.8956 | |
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| 0.0003 | 4.4156 | 340 | 0.4380 | 0.9231 | 0.8956 | |
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| 0.0003 | 4.6753 | 360 | 0.4406 | 0.9103 | 0.8803 | |
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| 0.0003 | 4.9351 | 380 | 0.4459 | 0.9231 | 0.8956 | |
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| 0.0002 | 5.1948 | 400 | 0.4472 | 0.9103 | 0.8803 | |
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| 0.0002 | 5.4545 | 420 | 0.4514 | 0.9103 | 0.8803 | |
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| 0.0002 | 5.7143 | 440 | 0.4550 | 0.9231 | 0.8956 | |
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| 0.0002 | 5.9740 | 460 | 0.4579 | 0.9231 | 0.8956 | |
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| 0.0002 | 6.2338 | 480 | 0.4600 | 0.9231 | 0.8956 | |
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| 0.0002 | 6.4935 | 500 | 0.4614 | 0.9103 | 0.8803 | |
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| 0.0002 | 6.7532 | 520 | 0.4637 | 0.9231 | 0.8956 | |
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| 0.0002 | 7.0130 | 540 | 0.4660 | 0.9231 | 0.8956 | |
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| 0.0002 | 7.2727 | 560 | 0.4684 | 0.9231 | 0.8956 | |
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| 0.0002 | 7.5325 | 580 | 0.4695 | 0.9231 | 0.8956 | |
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| 0.0002 | 7.7922 | 600 | 0.4710 | 0.9103 | 0.8803 | |
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| 0.0001 | 8.0519 | 620 | 0.4719 | 0.9103 | 0.8803 | |
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| 0.0001 | 8.3117 | 640 | 0.4726 | 0.9103 | 0.8803 | |
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| 0.0001 | 8.5714 | 660 | 0.4742 | 0.9103 | 0.8803 | |
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| 0.0001 | 8.8312 | 680 | 0.4754 | 0.9231 | 0.8956 | |
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| 0.0002 | 9.0909 | 700 | 0.4757 | 0.9231 | 0.8956 | |
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| 0.0001 | 9.3506 | 720 | 0.4759 | 0.9231 | 0.8956 | |
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| 0.0001 | 9.6104 | 740 | 0.4763 | 0.9231 | 0.8956 | |
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| 0.0001 | 9.8701 | 760 | 0.4765 | 0.9231 | 0.8956 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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