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: vit-base-patch16-224-in21k_GI_diagnosis
+  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: 0.88125
+---
+
+<!-- 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-patch16-224-in21k_GI_diagnosis
+
+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: 0.5797
+- Accuracy: 0.8812
+- Weighted f1: 0.8740
+- Micro f1: 0.8812
+- Macro f1: 0.8740
+- Weighted recall: 0.8812
+- Micro recall: 0.8812
+- Macro recall: 0.8813
+- Weighted precision: 0.9157
+- Micro precision: 0.8812
+- Macro precision: 0.9157
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 1.3805        | 1.0   | 200  | 0.5006          | 0.8638   | 0.8531      | 0.8638   | 0.8531   | 0.8638          | 0.8638       | 0.8638       | 0.9111             | 0.8638          | 0.9111          |
+| 1.3805        | 2.0   | 400  | 0.2538          | 0.9375   | 0.9365      | 0.9375   | 0.9365   | 0.9375          | 0.9375       | 0.9375       | 0.9455             | 0.9375          | 0.9455          |
+| 0.0628        | 3.0   | 600  | 0.5797          | 0.8812   | 0.8740      | 0.8812   | 0.8740   | 0.8812          | 0.8812       | 0.8813       | 0.9157             | 0.8812          | 0.9157          |
+
+
+### Framework versions
+
+- Transformers 4.22.2
+- Pytorch 1.12.1
+- Datasets 2.5.2
+- Tokenizers 0.12.1