update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- multi_news
+metrics:
+- rouge
+model-index:
+- name: bart_large_summarise_v3
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: multi_news
+      type: multi_news
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 0.3914
+---
+
+<!-- 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. -->
+
+# bart_large_summarise_v3
+
+This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the multi_news dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.1359
+- Rouge1: 0.3914
+- Rouge2: 0.1399
+- Rougel: 0.2039
+- Rougelsum: 0.3504
+- Gen Len: 141.64
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+- label_smoothing_factor: 0.1
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.23.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.6.1
+- Tokenizers 0.13.1