update model card README.md

README.md

@@ -3,26 +3,11 @@ license: apache-2.0
 base_model: t5-small
 tags:
 - generated_from_trainer
-datasets:
-- billsum
 metrics:
 - rouge
 model-index:
 - name: my_awesome_billsum_model
-  results:
-  - task:
-      name: Sequence-to-sequence Language Modeling
-      type: text2text-generation
-    dataset:
-      name: billsum
-      type: billsum
-      config: default
-      split: ca_test
-      args: default
-    metrics:
-    - name: Rouge1
-      type: rouge
-      value: 0.1409
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,14 +15,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 # my_awesome_billsum_model
 
-This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum 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: 2.5350
-- Rouge1: 0.1409
-- Rouge2: 0.0509
-- Rougel: 0.1163
-- Rougelsum: 0.1165
-- Gen Len: 19.0
+- Loss: 1.5768
+- Rouge1: 0.3454
+- Rouge2: 0.1108
+- Rougel: 0.2865
+- Rougelsum: 0.2866
+- Gen Len: 18.752
 
 ## Model description
 
@@ -68,10 +53,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
-| No log        | 1.0   | 62   | 2.8359          | 0.1219 | 0.0333 | 0.1029 | 0.1031    | 19.0    |
-| No log        | 2.0   | 124  | 2.6156          | 0.1363 | 0.0468 | 0.1131 | 0.1132    | 19.0    |
-| No log        | 3.0   | 186  | 2.5540          | 0.1398 | 0.0514 | 0.1154 | 0.1158    | 19.0    |
-| No log        | 4.0   | 248  | 2.5350          | 0.1409 | 0.0509 | 0.1163 | 0.1165    | 19.0    |
+| 1.7371        | 1.0   | 779  | 1.6408          | 0.3309 | 0.0977 | 0.2751 | 0.2751    | 18.79   |
+| 1.5146        | 2.0   | 1558 | 1.5945          | 0.3418 | 0.108  | 0.284  | 0.2842    | 18.766  |
+| 1.4889        | 3.0   | 2337 | 1.5801          | 0.3452 | 0.1113 | 0.2863 | 0.2864    | 18.742  |
+| 1.465         | 4.0   | 3116 | 1.5768          | 0.3454 | 0.1108 | 0.2865 | 0.2866    | 18.752  |
 
 
 ### Framework versions