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-cnn-finetuned-multi-news
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: multi_news
+      type: multi_news
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 42.0423
+---
+
+<!-- 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-cnn-finetuned-multi-news
+
+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: 2.0950
+- Rouge1: 42.0423
+- Rouge2: 14.8812
+- Rougel: 23.3412
+- Rougelsum: 36.2613
+
+## 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: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
+| 2.2037        | 1.0   | 750  | 2.0950          | 42.0423 | 14.8812 | 23.3412 | 36.2613   |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.0.0
+- Tokenizers 0.11.6