update model card README.md

README.md

@@ -2,6 +2,8 @@
 license: apache-2.0
 tags:
 - generated_from_trainer
+datasets:
+- generator
 model-index:
 - name: t5-small-finetuned-NL2ModelioMQ
   results: []
@@ -12,12 +14,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # t5-small-finetuned-NL2ModelioMQ
 
-This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the generator dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0277
-- Rouge2 Precision: 0.8832
-- Rouge2 Recall: 0.5437
-- Rouge2 Fmeasure: 0.6564
+- Loss: 0.0000
+- Rouge2 Precision: 0.9789
+- Rouge2 Recall: 0.6056
+- Rouge2 Fmeasure: 0.7296
 
 ## Model description
 
@@ -47,13 +49,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
-|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
-| No log        | 1.0   | 449  | 0.1599          | 0.6233           | 0.3954        | 0.4743          |
-| 0.6586        | 2.0   | 898  | 0.0732          | 0.7566           | 0.4653        | 0.5623          |
-| 0.177         | 3.0   | 1347 | 0.0430          | 0.8242           | 0.5091        | 0.6143          |
-| 0.1103        | 4.0   | 1796 | 0.0309          | 0.8738           | 0.5357        | 0.6478          |
-| 0.0859        | 5.0   | 2245 | 0.0277          | 0.8832           | 0.5437        | 0.6564          |
+| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
+|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
+| 0.0095        | 1.0   | 4449  | 0.0005          | 0.9702           | 0.6012        | 0.7238          |
+| 0.0015        | 2.0   | 8898  | 0.0000          | 0.9789           | 0.6056        | 0.7296          |
+| 0.0006        | 3.0   | 13347 | 0.0000          | 0.9789           | 0.6056        | 0.7296          |
+| 0.0004        | 4.0   | 17796 | 0.0000          | 0.9789           | 0.6056        | 0.7296          |
+| 0.0003        | 5.0   | 22245 | 0.0000          | 0.9789           | 0.6056        | 0.7296          |
 
 
 ### Framework versions