update model card README.md

README.md

@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [ku-nlp/bart-base-japanese](https://huggingface.co/ku-nlp/bart-base-japanese) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.3382
-- Rouge1: 3.8334
-- Rouge2: 0.7391
-- Rougel: 2.6123
-- Rougelsum: 3.4838
-- Gen Len: 19.0807
+- Loss: 3.5252
+- Rouge1: 11.814
+- Rouge2: 1.7965
+- Rougel: 8.0177
+- Rougelsum: 9.7342
+- Gen Len: 50.4446
 
 ## Model description
 
@@ -40,7 +40,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-06
+- learning_rate: 5e-05
 - train_batch_size: 1
 - eval_batch_size: 1
 - seed: 42
@@ -50,13 +50,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
-|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
-| 1.9773        | 1.0   | 4332  | 2.3066          | 2.1349 | 0.4575 | 1.5719 | 1.9249    | 9.6851  |
-| 1.5625        | 2.0   | 8664  | 2.2931          | 3.6283 | 0.7297 | 2.5484 | 3.285     | 14.8101 |
-| 1.3739        | 3.0   | 12996 | 2.3153          | 2.6835 | 0.5213 | 1.9015 | 2.5034    | 12.9794 |
-| 1.2579        | 4.0   | 17328 | 2.3374          | 3.4587 | 0.6968 | 2.3777 | 3.1843    | 17.7215 |
-| 1.2145        | 5.0   | 21660 | 2.3382          | 3.8334 | 0.7391 | 2.6123 | 3.4838    | 19.0807 |
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:|
+| 0.2994        | 1.0   | 4332  | 2.7883          | 11.1611 | 1.7768 | 7.5158 | 9.6222    | 55.0633 |
+| 0.1513        | 2.0   | 8664  | 3.1286          | 13.7182 | 2.311  | 9.1726 | 11.5058   | 57.3528 |
+| 0.0778        | 3.0   | 12996 | 3.3238          | 12.1173 | 1.88   | 8.1156 | 10.1187   | 48.7089 |
+| 0.056         | 4.0   | 17328 | 3.4032          | 11.9555 | 2.0536 | 8.2185 | 10.0656   | 50.7373 |
+| 0.0364        | 5.0   | 21660 | 3.5252          | 11.814  | 1.7965 | 8.0177 | 9.7342    | 50.4446 |
 
 
 ### Framework versions