Update README.md

README.md

@@ -7,12 +7,14 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # summarise_v6
 
-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: 1.0497
+- Rouge2 Precision: 0.3109
+- Rouge2 Recall: 0.406
+- Rouge2 Fmeasure: 0.3375
 
 ## Model description
 
@@ -32,12 +34,22 @@ 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 |
+|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
+| 1.7163        | 0.22  | 10   | 1.2307          | 0.1428           | 0.5118        | 0.2089          |
+| 1.632         | 0.44  | 20   | 1.1337          | 0.36             | 0.3393        | 0.3181          |
+| 1.0916        | 0.67  | 30   | 1.0738          | 0.2693           | 0.3487        | 0.2731          |
+| 1.573         | 0.89  | 40   | 1.0497          | 0.3109           | 0.406         | 0.3375          |
 
 ### Framework versions