update model card README.md

README.md

@@ -0,0 +1,81 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- pub_med_summarization_dataset
+metrics:
+- rouge
+model-index:
+- name: distilbart-cnn-12-3-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: 40.5642
+---
+
+<!-- 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-12-3-finetuned-pubmed
+
+This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-3](https://huggingface.co/sshleifer/distilbart-cnn-12-3) on the pub_med_summarization_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.1743
+- Rouge1: 40.5642
+- Rouge2: 16.9812
+- Rougel: 25.3449
+- Rougelsum: 36.46
+- Gen Len: 141.95
+
+## 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
+| 2.469         | 1.0   | 4000  | 2.2956          | 38.3713 | 15.2594 | 23.6734 | 34.1634   | 141.707  |
+| 2.2527        | 2.0   | 8000  | 2.1994          | 39.5939 | 16.2376 | 24.6363 | 35.5106   | 141.831  |
+| 2.0669        | 3.0   | 12000 | 2.1780          | 40.078  | 16.6705 | 25.1119 | 35.9605   | 141.8475 |
+| 1.9275        | 4.0   | 16000 | 2.1669          | 40.0825 | 16.6169 | 24.9702 | 36.0191   | 141.928  |
+| 1.8102        | 5.0   | 20000 | 2.1743          | 40.5642 | 16.9812 | 25.3449 | 36.46     | 141.95   |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.10.0+cu111
+- Datasets 1.18.3
+- Tokenizers 0.11.6