update model card README.md

README.md

@@ -19,8 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9393548387096774
-duplicated_from: transformersbook/distilbert-base-uncased-distilled-clinc
+      value: 0.9387096774193548
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -28,11 +27,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # distilbert-base-uncased-distilled-clinc
 
-This model is a fine-tuned with knowledge distillation version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. The model is used in Chapter 8: Making Transformers Efficient in Production in the [NLP with Transformers book](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/). You can find the full code in the accompanying [Github repository](https://github.com/nlp-with-transformers/notebooks/blob/main/08_model-compression.ipynb).
-
+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: 0.1005
-- Accuracy: 0.9394
+- Loss: 0.0878
+- Accuracy: 0.9387
 
 ## Model description
 
@@ -63,21 +61,21 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.9031        | 1.0   | 318  | 0.5745          | 0.7365   |
-| 0.4481        | 2.0   | 636  | 0.2856          | 0.8748   |
-| 0.2528        | 3.0   | 954  | 0.1798          | 0.9187   |
-| 0.176         | 4.0   | 1272 | 0.1398          | 0.9294   |
-| 0.1416        | 5.0   | 1590 | 0.1211          | 0.9348   |
-| 0.1243        | 6.0   | 1908 | 0.1116          | 0.9348   |
-| 0.1133        | 7.0   | 2226 | 0.1062          | 0.9377   |
-| 0.1075        | 8.0   | 2544 | 0.1035          | 0.9387   |
-| 0.1039        | 9.0   | 2862 | 0.1014          | 0.9381   |
-| 0.1018        | 10.0  | 3180 | 0.1005          | 0.9394   |
+| 1.0369        | 1.0   | 318  | 0.5902          | 0.6987   |
+| 0.4468        | 2.0   | 636  | 0.2434          | 0.8606   |
+| 0.2204        | 3.0   | 954  | 0.1412          | 0.9113   |
+| 0.1478        | 4.0   | 1272 | 0.1121          | 0.9252   |
+| 0.1206        | 5.0   | 1590 | 0.1010          | 0.93     |
+| 0.1086        | 6.0   | 1908 | 0.0947          | 0.9345   |
+| 0.1009        | 7.0   | 2226 | 0.0916          | 0.9368   |
+| 0.0966        | 8.0   | 2544 | 0.0896          | 0.9381   |
+| 0.0939        | 9.0   | 2862 | 0.0881          | 0.9390   |
+| 0.0928        | 10.0  | 3180 | 0.0878          | 0.9387   |
 
 
 ### Framework versions
 
 - Transformers 4.11.3
-- Pytorch 1.9.1+cu102
-- Datasets 1.13.0
+- Pytorch 2.0.0+cu118
+- Datasets 1.16.1
 - Tokenizers 0.10.3