update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Rouge1
       type: rouge
-      value: 27.58
+      value: 27.57
 ---
 
 <!-- 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 [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.6529
-- Rouge1: 27.58
-- Rouge2: 8.54
-- Rougel: 15.15
-- Rougelsum: 18.04
+- Loss: 2.9167
+- Rouge1: 27.57
+- Rouge2: 8.53
+- Rougel: 15.17
+- Rougelsum: 18.03
 
 ## Model description
 
@@ -56,18 +56,25 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5.6e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 8
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
-| 1.7313        | 1.0   | 2500 | 2.6529          | 27.58  | 8.54   | 15.15  | 18.04     |
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
+| 2.8539        | 1.0   | 1250  | 2.5026          | 27.57  | 8.53   | 15.17  | 18.03     |
+| 2.3547        | 2.0   | 2500  | 2.5102          | 27.57  | 8.53   | 15.17  | 18.03     |
+| 2.0079        | 3.0   | 3750  | 2.5593          | 27.57  | 8.53   | 15.17  | 18.03     |
+| 1.7303        | 4.0   | 5000  | 2.6260          | 27.57  | 8.53   | 15.17  | 18.03     |
+| 1.4993        | 5.0   | 6250  | 2.7184          | 27.57  | 8.53   | 15.17  | 18.03     |
+| 1.3136        | 6.0   | 7500  | 2.8246          | 27.57  | 8.53   | 15.17  | 18.03     |
+| 1.1718        | 7.0   | 8750  | 2.8684          | 27.57  | 8.53   | 15.17  | 18.03     |
+| 1.0729        | 8.0   | 10000 | 2.9167          | 27.57  | 8.53   | 15.17  | 18.03     |
 
 
 ### Framework versions