update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9379310344827586
+      value: 0.9354685646500593
     - name: Recall
       type: recall
-      value: 0.9579791110031577
+      value: 0.9577362156910372
     - name: F1
       type: f1
-      value: 0.9478490747416486
+      value: 0.9464714354296688
     - name: Accuracy
       type: accuracy
-      value: 0.9867005707595492
+      value: 0.986481047855993
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [sberbank-ai/ruBert-base](https://huggingface.co/sberbank-ai/ruBert-base) on the collection3 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0505
-- Precision: 0.9379
-- Recall: 0.9580
-- F1: 0.9478
-- Accuracy: 0.9867
+- Loss: 0.0514
+- Precision: 0.9355
+- Recall: 0.9577
+- F1: 0.9465
+- Accuracy: 0.9865
 
 ## Model description
 
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0814        | 1.0   | 1163 | 0.0531          | 0.9160    | 0.9483 | 0.9319 | 0.9828   |
-| 0.0395        | 2.0   | 2326 | 0.0536          | 0.9229    | 0.9599 | 0.9411 | 0.9854   |
-| 0.0203        | 3.0   | 3489 | 0.0505          | 0.9379    | 0.9580 | 0.9478 | 0.9867   |
+| 0.0794        | 1.0   | 1163 | 0.0536          | 0.9178    | 0.9466 | 0.9320 | 0.9825   |
+| 0.0391        | 2.0   | 2326 | 0.0512          | 0.9228    | 0.9553 | 0.9388 | 0.9853   |
+| 0.0191        | 3.0   | 3489 | 0.0514          | 0.9355    | 0.9577 | 0.9465 | 0.9865   |
 
 
 ### Framework versions