update model card README.md

README.md

@@ -1,3 +1,80 @@
 ---
-license: mit
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- arxiv_summarization_dataset
+metrics:
+- rouge
+model-index:
+- name: distilbart-cnn-12-6-finetuned-30k-3epoch
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: arxiv_summarization_dataset
+      type: arxiv_summarization_dataset
+      config: section
+      split: test[:2000]
+      args: section
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 43.696
 ---
+
+<!-- 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. -->
+
+# distilbart-cnn-12-6-finetuned-30k-3epoch
+
+This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the arxiv_summarization_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3411
+- Rouge1: 43.696
+- Rouge2: 15.6681
+- Rougel: 25.6889
+- Rougelsum: 38.574
+- Gen Len: 121.98
+
+## 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: 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 | Gen Len  |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
+| 2.7304        | 1.0   | 3750  | 2.4322          | 43.0913 | 15.1302 | 25.2555 | 38.0346   | 122.3755 |
+| 2.3518        | 2.0   | 7500  | 2.3613          | 43.8799 | 15.6977 | 25.6984 | 38.7646   | 122.6945 |
+| 2.2318        | 3.0   | 11250 | 2.3411          | 43.696  | 15.6681 | 25.6889 | 38.574    | 121.98   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3