Update README.md

README.md

@@ -31,15 +31,18 @@ This model is a fine-tuned version of [google/efficientnet-b5](https://huggingfa
 It achieves the following results on the evaluation set:
 - Loss: 0.9410
 - Accuracy: 0.8020
-- Weighted f1: 0.7736
-- Micro f1: 0.8020
-- Macro f1: 0.7802
-- Weighted recall: 0.8020
-- Micro recall: 0.8020
-- Macro recall: 0.7977
-- Weighted precision: 0.8535
-- Micro precision: 0.8020
-- Macro precision: 0.8682
+- F1
+  - Weighted: 0.7736
+  - Micro: 0.8020
+  - Macro: 0.7802
+- Recall
+  - Weighted: 0.8020
+  - Micro: 0.8020
+  - Macro: 0.7977
+- Precision
+  - Weighted: 0.8535
+  - Micro: 0.8020
+  - Macro: 0.8682
 
 <div style="text-align: center;">
 <h2>
@@ -93,7 +96,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
 | 1.3872        | 1.0   | 180  | 1.0601          | 0.6853   | 0.6485      | 0.6853   | 0.6550   | 0.6853          | 0.6853       | 0.6802       | 0.8177             | 0.6853          | 0.8330          |
 | 1.3872        | 2.0   | 360  | 0.9533          | 0.7843   | 0.7483      | 0.7843   | 0.7548   | 0.7843          | 0.7843       | 0.7819       | 0.8354             | 0.7843          | 0.8471          |