update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- beans
+metrics:
+- accuracy
+model-index:
+- name: vit-base-beans
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: beans
+      type: beans
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9699248120300752
+---
+
+<!-- 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-beans
+
+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 beans dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1151
+- Accuracy: 0.9699
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3365        | 0.38  | 50   | 0.2455          | 0.9323   |
+| 0.1728        | 0.77  | 100  | 0.1544          | 0.9549   |
+| 0.1519        | 1.15  | 150  | 0.1072          | 0.9624   |
+| 0.0209        | 1.54  | 200  | 0.1594          | 0.9624   |
+| 0.0206        | 1.92  | 250  | 0.0913          | 0.9699   |
+| 0.0135        | 2.31  | 300  | 0.1488          | 0.9624   |
+| 0.0079        | 2.69  | 350  | 0.0226          | 0.9925   |
+| 0.0074        | 3.08  | 400  | 0.0582          | 0.9925   |
+| 0.0064        | 3.46  | 450  | 0.0984          | 0.9774   |
+| 0.0061        | 3.85  | 500  | 0.1151          | 0.9699   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu117
+- Datasets 2.11.0
+- Tokenizers 0.13.3