Update README.md

README.md

@@ -1,7 +1,11 @@
 ---
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
+pipeline_tag: image-classification
 tags:
+- food101
+- vit
+- image-classification
 - generated_from_trainer
 metrics:
 - accuracy
@@ -9,57 +13,3 @@ model-index:
 - name: image_classification_food101VITmodel
   results: []
 ---
-
-<!-- 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. -->
-
-# image_classification_food101VITmodel
-
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 2.5424
-- Accuracy: 0.7
-
-## 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: 16
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 64
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 4.2504        | 0.96  | 12   | 3.4853          | 0.695    |
-| 3.1914        | 2.0   | 25   | 2.7080          | 0.695    |
-| 2.6501        | 2.88  | 36   | 2.5424          | 0.7      |
-
-
-### Framework versions
-
-- Transformers 4.35.2
-- Pytorch 2.1.0+cu121
-- Datasets 2.16.0
-- Tokenizers 0.15.0