update model card README.md

README.md

@@ -12,23 +12,24 @@ 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 the ModelioMQ dataset.
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0000
-- Rouge2 Precision: 0.9788
-- Rouge2 Recall: 0.6053
-- Rouge2 Fmeasure: 0.7294
+- Loss: 0.0755
+- Rouge2 Precision: 0.7481
+- Rouge2 Recall: 0.462
+- Rouge2 Fmeasure: 0.5577
 
 ## Model description
 
+More information needed
 
 ## Intended uses & limitations
 
-This model will be used to assist [Modelio](https://www.modelio.org/) users in writing model queries in the ModelioMQ language.
+More information needed
 
 ## Training and evaluation data
 
-The ModelioMQ dataset originates from 79 manually-written NL|ModelioMQ pairs, which have been augmentated using [NLPAug](https://github.com/makcedward/nlpaug)
+More information needed
 
 ## Training procedure
 
@@ -46,15 +47,16 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
-|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
-| 0.0104        | 1.0   | 4449  | 0.0006          | 0.9699           | 0.601         | 0.7235          |
-| 0.002         | 2.0   | 8898  | 0.0000          | 0.9788           | 0.6053        | 0.7294          |
-| 0.001         | 3.0   | 13347 | 0.0000          | 0.9788           | 0.6053        | 0.7294          |
+| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
+|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
+| No log        | 1.0   | 449  | 0.1696          | 0.6061           | 0.3886        | 0.4635          |
+| 0.653         | 2.0   | 898  | 0.0933          | 0.7231           | 0.4496        | 0.5415          |
+| 0.2028        | 3.0   | 1347 | 0.0755          | 0.7481           | 0.462         | 0.5577          |
 
 
 ### Framework versions
 
-- Transformers 4.24.0
-- Pytorch 1.12.1+cu113
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu116
+- Datasets 2.7.1
 - Tokenizers 0.13.2