Update README.md

README.md

@@ -20,15 +20,18 @@ This model is a fine-tuned version of [squeezebert/squeezebert-uncased](https://
 It achieves the following results on the evaluation set:
 - Loss: 0.2643
 - Accuracy: 0.9167
-- Weighted f1: 0.9166
-- Micro f1: 0.9167
-- Macro f1: 0.8749
-- Weighted recall: 0.9167
-- Micro recall: 0.9167
-- Macro recall: 0.8684
-- Weighted precision: 0.9168
-- Micro precision: 0.9167
-- Macro precision: 0.8822
+- F1
+  - Weighted: 0.9166
+  - Micro: 0.9167
+  - Macro: 0.8749
+- Recall
+  - Weighted: 0.9167
+  - Micro: 0.9167
+  - Macro: 0.8684
+- Precision
+  - Weighted: 0.9168
+  - Micro: 0.9167
+  - Macro: 0.8822
 
 ## Model description
 
@@ -67,7 +70,7 @@ 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
 | 0.8756        | 1.0   | 133  | 0.4529          | 0.8699   | 0.8557      | 0.8699   | 0.6560   | 0.8699          | 0.8699       | 0.6727       | 0.8437             | 0.8699          | 0.6414          |
 | 0.4097        | 2.0   | 266  | 0.3196          | 0.9026   | 0.8982      | 0.9026   | 0.7826   | 0.9026          | 0.9026       | 0.7635       | 0.9059             | 0.9026          | 0.8743          |