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_30
+  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: 0.8269230769230769
+    - name: F1
+      type: f1
+      value: 0.7314974182444062
+---
+
+<!-- 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_30
+
+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: 0.3936
+- Accuracy: 0.8269
+- F1: 0.7315
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
+| 0.5034        | 0.2597 | 20   | 0.4719          | 0.7436   | 0.4708 |
+| 0.4414        | 0.5195 | 40   | 0.4457          | 0.7821   | 0.6400 |
+| 0.3762        | 0.7792 | 60   | 0.4212          | 0.8205   | 0.7248 |
+| 0.4059        | 1.0390 | 80   | 0.3988          | 0.8462   | 0.7641 |
+| 0.3249        | 1.2987 | 100  | 0.3829          | 0.8333   | 0.7606 |
+| 0.2991        | 1.5584 | 120  | 0.4080          | 0.8462   | 0.7743 |
+| 0.2948        | 1.8182 | 140  | 0.3932          | 0.8462   | 0.7833 |
+| 0.2667        | 2.0779 | 160  | 0.4388          | 0.8333   | 0.7502 |
+| 0.2049        | 2.3377 | 180  | 0.4047          | 0.8333   | 0.7606 |
+| 0.1639        | 2.5974 | 200  | 0.4301          | 0.8333   | 0.7502 |
+| 0.1732        | 2.8571 | 220  | 0.4028          | 0.8333   | 0.7606 |
+| 0.1138        | 3.1169 | 240  | 0.3755          | 0.8718   | 0.8194 |
+| 0.1099        | 3.3766 | 260  | 0.4019          | 0.8590   | 0.7886 |
+| 0.1285        | 3.6364 | 280  | 0.3739          | 0.8590   | 0.7974 |
+| 0.1265        | 3.8961 | 300  | 0.3714          | 0.8590   | 0.8051 |
+| 0.0735        | 4.1558 | 320  | 0.3820          | 0.8718   | 0.8194 |
+| 0.0515        | 4.4156 | 340  | 0.3910          | 0.8462   | 0.7833 |
+| 0.0577        | 4.6753 | 360  | 0.3984          | 0.8462   | 0.7833 |
+| 0.0584        | 4.9351 | 380  | 0.4314          | 0.8590   | 0.7974 |
+| 0.0241        | 5.1948 | 400  | 0.4040          | 0.8718   | 0.8194 |
+| 0.015         | 5.4545 | 420  | 0.4201          | 0.8718   | 0.8194 |
+| 0.023         | 5.7143 | 440  | 0.4276          | 0.8718   | 0.8194 |
+| 0.0254        | 5.9740 | 460  | 0.4271          | 0.8846   | 0.8342 |
+| 0.0086        | 6.2338 | 480  | 0.4149          | 0.8718   | 0.8194 |
+| 0.012         | 6.4935 | 500  | 0.4738          | 0.8718   | 0.8120 |
+| 0.0052        | 6.7532 | 520  | 0.4314          | 0.8846   | 0.8342 |
+| 0.0123        | 7.0130 | 540  | 0.4363          | 0.8718   | 0.8194 |
+| 0.0026        | 7.2727 | 560  | 0.4477          | 0.8846   | 0.8342 |
+| 0.0018        | 7.5325 | 580  | 0.4447          | 0.8718   | 0.8194 |
+| 0.0024        | 7.7922 | 600  | 0.4588          | 0.8718   | 0.8194 |
+| 0.0076        | 8.0519 | 620  | 0.4517          | 0.8718   | 0.8194 |
+| 0.0013        | 8.3117 | 640  | 0.4535          | 0.8718   | 0.8194 |
+| 0.0012        | 8.5714 | 660  | 0.4479          | 0.8846   | 0.8342 |
+| 0.001         | 8.8312 | 680  | 0.4477          | 0.8846   | 0.8342 |
+| 0.0015        | 9.0909 | 700  | 0.4509          | 0.8846   | 0.8342 |
+| 0.001         | 9.3506 | 720  | 0.4529          | 0.8846   | 0.8342 |
+| 0.0009        | 9.6104 | 740  | 0.4569          | 0.8846   | 0.8342 |
+| 0.001         | 9.8701 | 760  | 0.4563          | 0.8846   | 0.8342 |
+
+
+### 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_15-16-43_d978789b493c/events.out.tfevents.1731165406.d978789b493c.30.0

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runs/Nov09_15-16-43_d978789b493c/events.out.tfevents.1731166529.d978789b493c.30.1

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training_args.bin

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