update model card README.md

README.md

@@ -12,12 +12,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # summarise_v6
 
-This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.0781
-- Rouge2 Precision: 0.3575
-- Rouge2 Recall: 0.2677
-- Rouge2 Fmeasure: 0.2899
+This model is a fine-tuned version of [debbiesoon/summarise](https://huggingface.co/debbiesoon/summarise) on an unknown dataset.
 
 ## Model description
 
@@ -37,23 +32,12 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 2
-- eval_batch_size: 2
+- 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
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
-|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
-| 1.735         | 0.22  | 10   | 1.3561          | 0.1706           | 0.4851        | 0.2442          |
-| 1.8028        | 0.44  | 20   | 1.1805          | 0.3464           | 0.2786        | 0.2879          |
-| 1.2608        | 0.67  | 30   | 1.1217          | 0.3634           | 0.309         | 0.3006          |
-| 1.5478        | 0.89  | 40   | 1.0781          | 0.3575           | 0.2677        | 0.2899          |
-
+- num_epochs: 3.0
 
 ### Framework versions