update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: microsoft/beit-large-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30-Shuffled
+  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: 0.9765227021040974
+---
+
+<!-- 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-Shuffled
+
+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: 0.0600
+- Accuracy: 0.9765
+
+## 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: 0.0005
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1531        | 0.99  | 93   | 0.1351          | 0.9506   |
+| 0.2389        | 1.99  | 187  | 0.1534          | 0.9344   |
+| 0.2517        | 3.0   | 281  | 0.1484          | 0.9402   |
+| 0.1769        | 4.0   | 375  | 0.1108          | 0.9570   |
+| 0.0764        | 4.96  | 465  | 0.0600          | 0.9765   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3