update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- pub_med_summarization_dataset
+metrics:
+- rouge
+model-index:
+- name: pegasus-large-finetuned-Pubmed
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: pub_med_summarization_dataset
+      type: pub_med_summarization_dataset
+      args: document
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 39.1107
+---
+
+<!-- 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. -->
+
+# pegasus-large-finetuned-Pubmed
+
+This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the pub_med_summarization_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7669
+- Rouge1: 39.1107
+- Rouge2: 15.4127
+- Rougel: 24.3729
+- Rougelsum: 35.1236
+- Gen Len: 226.594
+
+## 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: 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 2.065         | 1.0   | 1000 | 1.8262          | 37.1986 | 14.3685 | 23.7153 | 33.0713   | 218.902 |
+| 1.9552        | 2.0   | 2000 | 1.7933          | 38.0663 | 14.7813 | 23.8412 | 33.9574   | 217.488 |
+| 1.8983        | 3.0   | 3000 | 1.7768          | 38.3975 | 15.0983 | 24.0247 | 34.314    | 222.32  |
+| 1.882         | 4.0   | 4000 | 1.7687          | 39.1311 | 15.4167 | 24.2978 | 35.078    | 222.564 |
+| 1.8456        | 5.0   | 5000 | 1.7669          | 39.1107 | 15.4127 | 24.3729 | 35.1236   | 226.594 |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.9.1
+- Datasets 1.18.4
+- Tokenizers 0.11.6