update model card README.md

README.md

@@ -1,29 +1,12 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
-- vision
 - 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: 0.9924812030075187
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +15,6 @@ 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: 0.0841
-- Accuracy: 0.9925
 
 ## Model description
 
@@ -54,27 +34,16 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 1337
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 5.0
 
-### Training results
-
-| Training Loss | Epoch | Step | Accuracy | Validation Loss |
-|:-------------:|:-----:|:----:|:--------:|:---------------:|
-| 0.254         | 1.0   | 130  | 0.9624   | 0.2244          |
-| 0.2885        | 2.0   | 260  | 0.9925   | 0.1098          |
-| 0.1555        | 3.0   | 390  | 0.9850   | 0.1041          |
-| 0.092         | 4.0   | 520  | 0.9925   | 0.0818          |
-| 0.1591        | 5.0   | 650  | 0.9850   | 0.0826          |
-
-
 ### Framework versions
 
-- Transformers 4.28.1
+- Transformers 4.29.0
 - Pytorch 2.0.0+cu117
 - Datasets 2.11.0
 - Tokenizers 0.13.3