update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+model-index:
+- name: summarise_v6
+  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 [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
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- 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: 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          |
+
+
+### Framework versions
+
+- Transformers 4.21.3
+- Pytorch 1.12.1+cu113
+- Datasets 1.2.1
+- Tokenizers 0.12.1