update model card README.md

README.md

@@ -12,7 +12,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # summarise_v8
 
-This model is a fine-tuned version of [debbiesoon/summarise](https://huggingface.co/debbiesoon/summarise) on an unknown dataset.
+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: 0.8163
+- Rouge2 Precision: 0.3628
+- Rouge2 Recall: 0.3589
+- Rouge2 Fmeasure: 0.3316
 
 ## Model description
 
@@ -32,12 +37,23 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 2
+- eval_batch_size: 2
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3.0
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
+|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
+| 1.5952        | 0.23  | 10   | 1.0414          | 0.2823           | 0.3908        | 0.3013          |
+| 1.8116        | 0.47  | 20   | 0.9171          | 0.3728           | 0.273         | 0.3056          |
+| 1.6289        | 0.7   | 30   | 0.8553          | 0.3284           | 0.2892        | 0.291           |
+| 1.5074        | 0.93  | 40   | 0.8163          | 0.3628           | 0.3589        | 0.3316          |
+
 
 ### Framework versions