Update README.md

README.md

@@ -11,8 +11,8 @@ pipeline_tag: image-classification
 # Model Card for Model ID
 This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:
 <!-- Provide a quick summary of what the model is/does. -->
-<ul>Evaluation loss: 0.7166455984115601</ul>
-<ul>Accuracy: 0.8753663366336634</ul>
+- **Evaluation loss:** 0.7166455984115601
+- **Accuracy:** 0.8753663366336634
 
 
 ## Model Details
@@ -44,18 +44,18 @@ A model that can detect 101 variety of food.
 
 The following hyperparameters were used during training:
 
-<ul>-**learning_rate:** 5e-05</ul>
-<ul>-**train_batch_size**: 16</ul>
-<ul>-**seed:** 42</ul>
-<ul>-**optimizer:** Adam with betas=(0.9,0.999) and epsilon=1e-08</ul>
-<ul>-**lr_scheduler_type:** linear</ul>
-<ul>-**num_epochs:** 1</ul>
+- **learning_rate:** 5e-05
+- **train_batch_size**: 16
+- **seed:** 42
+- **optimizer:** Adam with betas=(0.9,0.999) and epsilon=1e-08
+- **lr_scheduler_type:** linear
+- **num_epochs:** 1
 
 ## Evaluation
 
 <!-- This section describes the evaluation protocols and provides the results. -->
-<ul>-**eval_loss:** 0.7166455984115601</ul>
-<ul>-**eval_accuracy:** 0.8753663366336634 </ul>
-<ul>-**eval_runtime:** 446.9362</ul>
-<ul>-**eval_steps_per_second:** 3.533</ul>
-<ul>-**epoch:** 1.0</ul>
+- **eval_loss:** 0.7166455984115601
+- **eval_accuracy:** 0.8753663366336634 
+- **eval_runtime:** 446.9362
+- **eval_steps_per_second:** 3.533
+- **epoch:** 1.0