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
+  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: 0.8653846153846154
+    - name: F1
+      type: f1
+      value: 0.8156962025316457
+---
+
+<!-- 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
+
+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: 0.3570
+- Accuracy: 0.8654
+- F1: 0.8157
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 8
+- 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
+| 0.5391        | 0.5556 | 10   | 0.4007          | 0.7949   | 0.6698 |
+| 0.3685        | 1.1111 | 20   | 0.3650          | 0.8718   | 0.8120 |
+| 0.2275        | 1.6667 | 30   | 0.3601          | 0.8462   | 0.8101 |
+| 0.1604        | 2.2222 | 40   | 0.2938          | 0.8718   | 0.8319 |
+| 0.0624        | 2.7778 | 50   | 0.2966          | 0.8846   | 0.8511 |
+| 0.0597        | 3.3333 | 60   | 0.4313          | 0.8974   | 0.8556 |
+| 0.029         | 3.8889 | 70   | 0.4105          | 0.8718   | 0.8194 |
+| 0.0094        | 4.4444 | 80   | 0.3746          | 0.9103   | 0.8803 |
+| 0.0077        | 5.0    | 90   | 0.4098          | 0.8974   | 0.8655 |
+| 0.0082        | 5.5556 | 100  | 0.4451          | 0.9103   | 0.8803 |
+| 0.0024        | 6.1111 | 110  | 0.4599          | 0.8974   | 0.8655 |
+| 0.0028        | 6.6667 | 120  | 0.4739          | 0.8974   | 0.8608 |
+| 0.0013        | 7.2222 | 130  | 0.4653          | 0.8974   | 0.8655 |
+| 0.0016        | 7.7778 | 140  | 0.4927          | 0.8974   | 0.8608 |
+| 0.0011        | 8.3333 | 150  | 0.5115          | 0.8974   | 0.8608 |
+| 0.0015        | 8.8889 | 160  | 0.5055          | 0.8974   | 0.8608 |
+| 0.0007        | 9.4444 | 170  | 0.4982          | 0.8974   | 0.8608 |
+| 0.0011        | 10.0   | 180  | 0.4975          | 0.8974   | 0.8608 |
+
+
+### 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/Oct19_02-25-41_120f3e0b8117/events.out.tfevents.1729304744.120f3e0b8117.23.0

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runs/Oct19_02-25-41_120f3e0b8117/events.out.tfevents.1729304913.120f3e0b8117.23.1

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training_args.bin

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