update model card README.md

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9438709677419355
+      value: 0.9306451612903226
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2108
-- Accuracy: 0.9439
+- Loss: 0.0376
+- Accuracy: 0.9306
 
 ## Model description
 
@@ -55,21 +55,22 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 9
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.0011        | 1.0   | 318  | 1.4515          | 0.7655   |
-| 1.142         | 2.0   | 636  | 0.7762          | 0.87     |
-| 0.6315        | 3.0   | 954  | 0.4564          | 0.9171   |
-| 0.3865        | 4.0   | 1272 | 0.3170          | 0.9329   |
-| 0.2678        | 5.0   | 1590 | 0.2573          | 0.9426   |
-| 0.2125        | 6.0   | 1908 | 0.2316          | 0.9432   |
-| 0.184         | 7.0   | 2226 | 0.2185          | 0.9432   |
-| 0.1699        | 8.0   | 2544 | 0.2124          | 0.9445   |
-| 0.1638        | 9.0   | 2862 | 0.2108          | 0.9439   |
+| 0.819         | 1.0   | 318  | 0.4220          | 0.6687   |
+| 0.3215        | 2.0   | 636  | 0.1501          | 0.8429   |
+| 0.149         | 3.0   | 954  | 0.0783          | 0.9019   |
+| 0.0958        | 4.0   | 1272 | 0.0571          | 0.9132   |
+| 0.0751        | 5.0   | 1590 | 0.0484          | 0.9229   |
+| 0.0649        | 6.0   | 1908 | 0.0437          | 0.9281   |
+| 0.059         | 7.0   | 2226 | 0.0408          | 0.9313   |
+| 0.0553        | 8.0   | 2544 | 0.0390          | 0.93     |
+| 0.0532        | 9.0   | 2862 | 0.0379          | 0.9313   |
+| 0.0518        | 10.0  | 3180 | 0.0376          | 0.9306   |
 
 
 ### Framework versions