Update README.md

README.md

@@ -15,26 +15,36 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on an [custom](https://www.kaggle.com/datasets/faldoae/padangfood) dataset. This model was built using the "Padang Cuisine (Indonesian Food Image Classification)" dataset obtained from Kaggle. During the model building process, this was done using the Pytorch framework with pre-trained Resnet-18. The method used during the process of building this classification model is fine-tuning with the dataset.
 
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
+## Training results
+
+| Epoch | Accuracy |
+|:-----:|:--------:|
+| 1.0   | 0.6030   |
+| 2.0   | 0.8342   |
+| 3.0   | 0.8442   |
+| 4.0   | 0.8191   |
+| 5.0   | 0.8693   |
+| 6.0   | 0.8643   |
+| 7.0   | 0.8744   |
+| 8.0   | 0.8643   |
+| 9.0   | 0.8744   |
+| 10.0  | 0.8744   |
+| 11.0  | 0.8794   |
+| 12.0  | 0.8744   |
+| 13.0  | 0.8894   |
+| 14.0  | 0.8794   |
+| 15.0  | 0.8945   |
 
 ## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- 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: 3.0
+- loss_function = CrossEntropyLoss
+- optimizer = AdamW
+- learning_rate: 0.00001
+- batch_size: 16
+- num_epochs: 15
 
 ### Framework versions