End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Rouge1
       type: rouge
-      value: 0.1426
+      value: 0.1117
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,11 +32,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
 It achieves the following results on the evaluation set:
-- Loss: 3.8810
-- Rouge1: 0.1426
-- Rouge2: 0.0468
-- Rougel: 0.1256
-- Rougelsum: 0.1255
+- Loss: 2.9403
+- Rouge1: 0.1117
+- Rouge2: 0.0199
+- Rougel: 0.0955
+- Rougelsum: 0.0951
 - Gen Len: 19.0
 
 ## Model description
@@ -62,16 +62,32 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 4
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
-| No log        | 1.0   | 10   | 4.4927          | 0.1388 | 0.0377 | 0.1149 | 0.1142    | 19.0    |
-| No log        | 2.0   | 20   | 4.1105          | 0.1373 | 0.0377 | 0.1157 | 0.115     | 19.0    |
-| No log        | 3.0   | 30   | 3.9318          | 0.1407 | 0.0407 | 0.118  | 0.1175    | 19.0    |
-| No log        | 4.0   | 40   | 3.8810          | 0.1426 | 0.0468 | 0.1256 | 0.1255    | 19.0    |
+| No log        | 1.0   | 10   | 4.4002          | 0.1333 | 0.0378 | 0.1094 | 0.109     | 19.0    |
+| No log        | 2.0   | 20   | 3.8225          | 0.1325 | 0.0351 | 0.1085 | 0.1081    | 19.0    |
+| No log        | 3.0   | 30   | 3.5343          | 0.1343 | 0.0361 | 0.1109 | 0.1109    | 19.0    |
+| No log        | 4.0   | 40   | 3.3920          | 0.1253 | 0.0307 | 0.1069 | 0.1067    | 19.0    |
+| No log        | 5.0   | 50   | 3.2849          | 0.1239 | 0.0275 | 0.1028 | 0.103     | 19.0    |
+| No log        | 6.0   | 60   | 3.2041          | 0.1227 | 0.0237 | 0.1015 | 0.1016    | 19.0    |
+| No log        | 7.0   | 70   | 3.1439          | 0.1234 | 0.0218 | 0.1022 | 0.1023    | 19.0    |
+| No log        | 8.0   | 80   | 3.0979          | 0.1286 | 0.026  | 0.1057 | 0.106     | 19.0    |
+| No log        | 9.0   | 90   | 3.0624          | 0.1298 | 0.0289 | 0.1048 | 0.105     | 19.0    |
+| No log        | 10.0  | 100  | 3.0351          | 0.1286 | 0.0299 | 0.105  | 0.1053    | 19.0    |
+| No log        | 11.0  | 110  | 3.0135          | 0.1292 | 0.0288 | 0.1066 | 0.1068    | 19.0    |
+| No log        | 12.0  | 120  | 2.9956          | 0.1148 | 0.0195 | 0.0942 | 0.0938    | 19.0    |
+| No log        | 13.0  | 130  | 2.9813          | 0.1167 | 0.0195 | 0.0943 | 0.0939    | 19.0    |
+| No log        | 14.0  | 140  | 2.9697          | 0.1129 | 0.0204 | 0.0935 | 0.093     | 19.0    |
+| No log        | 15.0  | 150  | 2.9606          | 0.1129 | 0.0204 | 0.0935 | 0.093     | 19.0    |
+| No log        | 16.0  | 160  | 2.9534          | 0.1125 | 0.0198 | 0.0934 | 0.0931    | 19.0    |
+| No log        | 17.0  | 170  | 2.9478          | 0.1117 | 0.0199 | 0.0955 | 0.0951    | 19.0    |
+| No log        | 18.0  | 180  | 2.9436          | 0.1117 | 0.0199 | 0.0955 | 0.0951    | 19.0    |
+| No log        | 19.0  | 190  | 2.9411          | 0.1117 | 0.0199 | 0.0955 | 0.0951    | 19.0    |
+| No log        | 20.0  | 200  | 2.9403          | 0.1117 | 0.0199 | 0.0955 | 0.0951    | 19.0    |
 
 
 ### Framework versions

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