cutoutCLAHE

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- image-classification
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vit-base-finetuned-cephalometric
+  results: []
+---
+
+<!-- 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-base-finetuned-cephalometric
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the cepha-cutoutCLAHE dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7340
+- Accuracy: 0.6528
+
+## 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: 0.0001
+- train_batch_size: 32
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 16   | 0.9458          | 0.5486   |
+| 0.9879        | 2.0   | 32   | 0.6947          | 0.6597   |
+| 0.4628        | 3.0   | 48   | 0.6375          | 0.6597   |
+| 0.135         | 4.0   | 64   | 0.7060          | 0.6944   |
+| 0.0339        | 5.0   | 80   | 0.7301          | 0.6597   |
+| 0.0339        | 6.0   | 96   | 0.9236          | 0.6875   |
+| 0.0059        | 7.0   | 112  | 0.9261          | 0.6806   |
+| 0.0024        | 8.0   | 128  | 0.9961          | 0.6875   |
+| 0.0012        | 9.0   | 144  | 1.0060          | 0.6736   |
+| 0.0008        | 10.0  | 160  | 1.0329          | 0.6875   |
+| 0.0008        | 11.0  | 176  | 1.0575          | 0.6944   |
+| 0.0006        | 12.0  | 192  | 1.0768          | 0.6944   |
+| 0.0006        | 13.0  | 208  | 1.1002          | 0.6944   |
+| 0.0005        | 14.0  | 224  | 1.1220          | 0.6875   |
+| 0.0004        | 15.0  | 240  | 1.1367          | 0.6875   |
+| 0.0004        | 16.0  | 256  | 1.1538          | 0.6875   |
+| 0.0004        | 17.0  | 272  | 1.1707          | 0.6875   |
+| 0.0003        | 18.0  | 288  | 1.1855          | 0.6875   |
+| 0.0003        | 19.0  | 304  | 1.2007          | 0.6875   |
+| 0.0003        | 20.0  | 320  | 1.2066          | 0.6806   |
+| 0.0003        | 21.0  | 336  | 1.2211          | 0.6806   |
+| 0.0003        | 22.0  | 352  | 1.2291          | 0.6875   |
+| 0.0002        | 23.0  | 368  | 1.2385          | 0.6875   |
+| 0.0002        | 24.0  | 384  | 1.2508          | 0.6875   |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0

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": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "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": "4.48.3"
+}

model.safetensors

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preprocessor_config.json

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+{
+  "do_convert_rgb": null,
+  "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/Mar01_09-15-34_a31d1e9f3617/events.out.tfevents.1740820535.a31d1e9f3617.33093.0

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training_args.bin

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