End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9541284403669725
+      value: 0.9575688073394495
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3623
-- Accuracy: 0.9541
+- Loss: 0.6867
+- Accuracy: 0.9576
 
 ## Model description
 
@@ -68,19 +68,19 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.2263        | 0.38  | 50   | 0.1874          | 0.9404   |
-| 0.1549        | 0.76  | 100  | 0.1661          | 0.9438   |
-| 0.1321        | 1.14  | 150  | 0.3832          | 0.9484   |
-| 0.1153        | 1.52  | 200  | 0.2551          | 0.9484   |
-| 0.1135        | 1.89  | 250  | 0.1375          | 0.9530   |
-| 0.0823        | 2.27  | 300  | 0.4848          | 0.9495   |
-| 0.1417        | 2.65  | 350  | 0.3618          | 0.9484   |
-| 0.0763        | 3.03  | 400  | 0.3594          | 0.9530   |
-| 0.0959        | 3.41  | 450  | 0.3692          | 0.9576   |
-| 0.0925        | 3.79  | 500  | 0.3623          | 0.9541   |
-| 0.1089        | 4.17  | 550  | 0.4750          | 0.9576   |
-| 0.0758        | 4.55  | 600  | 0.8276          | 0.9472   |
-| 0.0792        | 4.92  | 650  | 0.5894          | 0.9553   |
+| 0.2069        | 0.38  | 50   | 0.4171          | 0.9438   |
+| 0.1627        | 0.76  | 100  | 0.3713          | 0.9518   |
+| 0.1641        | 1.14  | 150  | 0.4802          | 0.9553   |
+| 0.1261        | 1.52  | 200  | 0.2517          | 0.9541   |
+| 0.128         | 1.89  | 250  | 0.2427          | 0.9633   |
+| 0.0765        | 2.27  | 300  | 0.5854          | 0.9622   |
+| 0.1547        | 2.65  | 350  | 0.6896          | 0.9507   |
+| 0.0705        | 3.03  | 400  | 0.5790          | 0.9484   |
+| 0.0683        | 3.41  | 450  | 0.3680          | 0.9564   |
+| 0.0889        | 3.79  | 500  | 0.6867          | 0.9576   |
+| 0.1541        | 4.17  | 550  | 0.6979          | 0.9576   |
+| 0.0689        | 4.55  | 600  | 0.9328          | 0.9507   |
+| 0.0964        | 4.92  | 650  | 0.6852          | 0.9587   |
 
 
 ### Framework versions