update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- image_folder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224-in21k-finetuned-cassava3
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8852803738317757
+---
+
+<!-- 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-finetuned-cassava3
+
+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 image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3403
+- Accuracy: 0.8853
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5624        | 0.99  | 133  | 0.5866          | 0.8166   |
+| 0.4717        | 1.99  | 266  | 0.4245          | 0.8692   |
+| 0.4105        | 2.99  | 399  | 0.3708          | 0.8811   |
+| 0.3753        | 3.99  | 532  | 0.3646          | 0.8787   |
+| 0.2997        | 4.99  | 665  | 0.3655          | 0.8780   |
+| 0.3176        | 5.99  | 798  | 0.3545          | 0.8822   |
+| 0.2849        | 6.99  | 931  | 0.3441          | 0.8850   |
+| 0.2931        | 7.99  | 1064 | 0.3419          | 0.8855   |
+| 0.27          | 8.99  | 1197 | 0.3419          | 0.8848   |
+| 0.2927        | 9.99  | 1330 | 0.3403          | 0.8853   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1