update model card README.md

README.md

@@ -7,7 +7,7 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: distilbert-base-uncased-distilled-clinc
+- name: distilbert-base-uncased-finetuned-clinc
   results:
   - task:
       name: Text Classification
@@ -19,18 +19,18 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9432258064516129
+      value: 0.9174193548387096
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# distilbert-base-uncased-distilled-clinc
+# distilbert-base-uncased-finetuned-clinc
 
 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: 0.1770
-- Accuracy: 0.9432
+- Loss: 0.7773
+- Accuracy: 0.9174
 
 ## Model description
 
@@ -55,22 +55,17 @@ 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: 10
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.5226        | 1.0   | 318  | 0.9867          | 0.7287   |
-| 0.76          | 2.0   | 636  | 0.4736          | 0.8561   |
-| 0.3972        | 3.0   | 954  | 0.2794          | 0.9126   |
-| 0.2541        | 4.0   | 1272 | 0.2189          | 0.9294   |
-| 0.2017        | 5.0   | 1590 | 0.1971          | 0.9361   |
-| 0.1805        | 6.0   | 1908 | 0.1880          | 0.9406   |
-| 0.1685        | 7.0   | 2226 | 0.1826          | 0.9413   |
-| 0.1626        | 8.0   | 2544 | 0.1799          | 0.9426   |
-| 0.1589        | 9.0   | 2862 | 0.1782          | 0.9429   |
-| 0.1569        | 10.0  | 3180 | 0.1770          | 0.9432   |
+| 4.2923        | 1.0   | 318  | 3.2893          | 0.7423   |
+| 2.6307        | 2.0   | 636  | 1.8837          | 0.8281   |
+| 1.5483        | 3.0   | 954  | 1.1583          | 0.8968   |
+| 1.0153        | 4.0   | 1272 | 0.8618          | 0.9094   |
+| 0.7958        | 5.0   | 1590 | 0.7773          | 0.9174   |
 
 
 ### Framework versions