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_vegetables_classification
+  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: 1.0
+---
+
+<!-- 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_vegetables_classification
+
+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: 0.0014
+- Accuracy: 1.0
+- Weighted f1: 1.0
+- Micro f1: 1.0
+- Macro f1: 1.0
+- Weighted recall: 1.0
+- Micro recall: 1.0
+- Macro recall: 1.0
+- Weighted precision: 1.0
+- Micro precision: 1.0
+- Macro precision: 1.0
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 0.2079        | 1.0   | 938  | 0.0193          | 0.996    | 0.9960      | 0.996    | 0.9960   | 0.996           | 0.996        | 0.9960       | 0.9960             | 0.996           | 0.9960          |
+| 0.0154        | 2.0   | 1876 | 0.0068          | 0.9987   | 0.9987      | 0.9987   | 0.9987   | 0.9987          | 0.9987       | 0.9987       | 0.9987             | 0.9987          | 0.9987          |
+| 0.0018        | 3.0   | 2814 | 0.0014          | 1.0      | 1.0         | 1.0      | 1.0      | 1.0             | 1.0          | 1.0          | 1.0                | 1.0             | 1.0             |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.12.1
+- Datasets 2.8.0
+- Tokenizers 0.12.1