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End of training

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README.md ADDED
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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_15
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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: 0.7884615384615384
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+ - name: F1
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+ type: f1
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+ value: 0.6551215917464996
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+ ---
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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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+
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+ # ViT_breastmnist_std_15
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+
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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: 0.4504
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+ - Accuracy: 0.7885
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+ - F1: 0.6551
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.4628 | 0.2597 | 20 | 0.4724 | 0.7821 | 0.5951 |
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+ | 0.3645 | 0.5195 | 40 | 0.3994 | 0.8590 | 0.7786 |
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+ | 0.2744 | 0.7792 | 60 | 0.4429 | 0.8462 | 0.7524 |
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+ | 0.3004 | 1.0390 | 80 | 0.3893 | 0.8590 | 0.7886 |
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+ | 0.2153 | 1.2987 | 100 | 0.4120 | 0.8462 | 0.7641 |
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+ | 0.1593 | 1.5584 | 120 | 0.4542 | 0.8590 | 0.7786 |
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+ | 0.1189 | 1.8182 | 140 | 0.3911 | 0.8718 | 0.8120 |
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+ | 0.1139 | 2.0779 | 160 | 0.4154 | 0.8590 | 0.7886 |
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+ | 0.0707 | 2.3377 | 180 | 0.4517 | 0.8590 | 0.7886 |
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+ | 0.0482 | 2.5974 | 200 | 0.4824 | 0.8718 | 0.8034 |
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+ | 0.0499 | 2.8571 | 220 | 0.4408 | 0.8462 | 0.7743 |
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+ | 0.0195 | 3.1169 | 240 | 0.4874 | 0.8462 | 0.7743 |
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+ | 0.0146 | 3.3766 | 260 | 0.4723 | 0.8718 | 0.8120 |
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+ | 0.0141 | 3.6364 | 280 | 0.5117 | 0.8590 | 0.7886 |
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+ | 0.017 | 3.8961 | 300 | 0.6032 | 0.8462 | 0.7743 |
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+ | 0.0052 | 4.1558 | 320 | 0.5948 | 0.8590 | 0.7886 |
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+ | 0.005 | 4.4156 | 340 | 0.5897 | 0.8590 | 0.7886 |
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+ | 0.0039 | 4.6753 | 360 | 0.5729 | 0.8462 | 0.7743 |
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+ | 0.0088 | 4.9351 | 380 | 0.5623 | 0.8462 | 0.7743 |
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+ | 0.0104 | 5.1948 | 400 | 0.4814 | 0.8718 | 0.8194 |
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+ | 0.0012 | 5.4545 | 420 | 0.5039 | 0.8718 | 0.8194 |
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+ | 0.001 | 5.7143 | 440 | 0.5268 | 0.8718 | 0.8120 |
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+ | 0.001 | 5.9740 | 460 | 0.5435 | 0.8590 | 0.7886 |
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+ | 0.0007 | 6.2338 | 480 | 0.5435 | 0.8462 | 0.7743 |
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+ | 0.0007 | 6.4935 | 500 | 0.5373 | 0.8590 | 0.7974 |
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+ | 0.0006 | 6.7532 | 520 | 0.5745 | 0.8590 | 0.7886 |
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+ | 0.0007 | 7.0130 | 540 | 0.5674 | 0.8462 | 0.7743 |
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+ | 0.0004 | 7.2727 | 560 | 0.5826 | 0.8462 | 0.7743 |
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+ | 0.0006 | 7.5325 | 580 | 0.5663 | 0.8462 | 0.7743 |
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+ | 0.0006 | 7.7922 | 600 | 0.5751 | 0.8462 | 0.7743 |
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+ | 0.0005 | 8.0519 | 620 | 0.5851 | 0.8462 | 0.7743 |
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+ | 0.0004 | 8.3117 | 640 | 0.5782 | 0.8462 | 0.7743 |
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+ | 0.0004 | 8.5714 | 660 | 0.5875 | 0.8462 | 0.7743 |
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+ | 0.0004 | 8.8312 | 680 | 0.5939 | 0.8462 | 0.7743 |
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+ | 0.0004 | 9.0909 | 700 | 0.5934 | 0.8462 | 0.7743 |
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+ | 0.0004 | 9.3506 | 720 | 0.5925 | 0.8462 | 0.7743 |
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+ | 0.0004 | 9.6104 | 740 | 0.5930 | 0.8462 | 0.7743 |
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+ | 0.0004 | 9.8701 | 760 | 0.5945 | 0.8462 | 0.7743 |
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+
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+
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+ ### Framework versions
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+
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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
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "malignant": "0",
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+ "normal, benign": "1"
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.45.1"
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+ }
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