update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- reddit
+metrics:
+- rouge
+model-index:
+- name: pegasus-xsum-reddit-clean-4
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: reddit
+      type: reddit
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 27.7525
+---
+
+<!-- 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-xsum-reddit-clean-4
+
+This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the reddit dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.7697
+- Rouge1: 27.7525
+- Rouge2: 7.9823
+- Rougel: 20.9276
+- Rougelsum: 22.6678
+
+## 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: 5.6e-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
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
+| 3.0594        | 1.0   | 1906 | 2.8489          | 27.9837 | 8.0824 | 20.9135 | 22.7261   |
+| 2.861         | 2.0   | 3812 | 2.7793          | 27.8298 | 8.048  | 20.8653 | 22.6781   |
+| 2.7358        | 3.0   | 5718 | 2.7697          | 27.7525 | 7.9823 | 20.9276 | 22.6678   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1