End of training

README.md

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+---
+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

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "malignant",
+    "1": "normal, benign"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "malignant": "0",
+    "normal, benign": "1"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.1"
+}

model.safetensors

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+size 343223968

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

runs/Nov09_09-46-11_98124c9a2a99/events.out.tfevents.1731145573.98124c9a2a99.30.0

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training_args.bin

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