End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: image_classification_for_fracture
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.85
+---
+
+<!-- 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. -->
+
+# image_classification_for_fracture
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4783
+- Accuracy: 0.85
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.8   | 2    | 0.6696          | 0.75     |
+| No log        | 2.0   | 5    | 0.6296          | 0.7      |
+| No log        | 2.8   | 7    | 0.5853          | 0.775    |
+| 0.639         | 4.0   | 10   | 0.5731          | 0.8      |
+| 0.639         | 4.8   | 12   | 0.5430          | 0.825    |
+| 0.639         | 6.0   | 15   | 0.5223          | 0.85     |
+| 0.639         | 6.8   | 17   | 0.5036          | 0.8      |
+| 0.5453        | 8.0   | 20   | 0.4783          | 0.85     |
+
+
+### Framework versions
+
+- Transformers 4.39.1
+- Pytorch 2.2.1+cpu
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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