update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- pub_med_summarization_dataset
+metrics:
+- rouge
+model-index:
+- name: distilbart-cnn-12-6-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: 40.0985
+---
+
+<!-- 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-pubmed
+
+This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the pub_med_summarization_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9895
+- Rouge1: 40.0985
+- Rouge2: 16.5016
+- Rougel: 24.8319
+- Rougelsum: 36.0775
+- Gen Len: 141.884
+
+## 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  |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
+| 2.1709        | 1.0   | 4000  | 2.0257          | 38.1012 | 15.112  | 23.4064 | 33.9373   | 141.9195 |
+| 1.9495        | 2.0   | 8000  | 1.9593          | 39.529  | 16.1693 | 24.487  | 35.5238   | 141.9785 |
+| 1.756         | 3.0   | 12000 | 1.9488          | 39.9623 | 16.5799 | 24.949  | 35.9194   | 141.8855 |
+| 1.6032        | 4.0   | 16000 | 1.9732          | 39.672  | 16.1994 | 24.5996 | 35.7021   | 141.921  |
+| 1.4817        | 5.0   | 20000 | 1.9895          | 40.0985 | 16.5016 | 24.8319 | 36.0775   | 141.884  |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.10.0+cu111
+- Datasets 1.18.3
+- Tokenizers 0.11.6