update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: Augmented-Final
+      split: train
+      args: Augmented-Final
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9995570321151717
+---
+
+<!-- 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. -->
+
+# beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30
+
+This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0011
+- Accuracy: 0.9996
+
+## 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: 0.5
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0508        | 0.99  | 93   | 0.0634          | 0.9756   |
+| 0.0909        | 1.99  | 187  | 0.0222          | 0.9911   |
+| 0.0641        | 3.0   | 281  | 0.0228          | 0.9914   |
+| 0.0717        | 4.0   | 375  | 0.0050          | 0.9982   |
+| 0.0012        | 4.96  | 465  | 0.0011          | 0.9996   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3