update model card README.md

README.md

@@ -1,18 +1,12 @@
 ---
 license: apache-2.0
 tags:
-- text-classification
 - generated_from_trainer
 datasets:
 - glue
 metrics:
 - accuracy
 - f1
-widget:
- - text: ["Yucaipa owned Dominick 's before selling the chain to Safeway in 1998 for $ 2.5 billion.","Yucaipa bought Dominick's in 1995 for $ 693 million and sold it to Safeway for $ 1.8 billion in 1998."]
-   example_title: Not Equivalent
- - text: ["Revenue in the first quarter of the year dropped 15 percent from the same period a year earlier.", "With the scandal hanging over Stewart's company revenue the first quarter of the year dropped 15 percent from the same period a year earlier."]
-   example_title: Equivalent
 model-index:
 - name: platzi-distilroberta-base-mrpc-glue-omar-espejel
   results:
@@ -28,10 +22,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8553921568627451
+      value: 0.8431372549019608
     - name: F1
       type: f1
-      value: 0.897391304347826
+      value: 0.8861209964412811
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -39,11 +33,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # platzi-distilroberta-base-mrpc-glue-omar-espejel
 
-This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue and the mrpc datasets.
+This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6342
-- Accuracy: 0.8554
-- F1: 0.8974
+- Loss: 0.6332
+- Accuracy: 0.8431
+- F1: 0.8861
 
 ## Model description
 
@@ -74,8 +68,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.5004        | 1.09  | 500  | 0.6371          | 0.8113   | 0.8715 |
-| 0.33          | 2.18  | 1000 | 0.6342          | 0.8554   | 0.8974 |
+| 0.5076        | 1.09  | 500  | 0.7464          | 0.8137   | 0.8671 |
+| 0.3443        | 2.18  | 1000 | 0.6332          | 0.8431   | 0.8861 |
 
 
 ### Framework versions