Create README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- samsum
+metrics:
+- rouge
+model-index:
+- name: bart-large-cnn-samsum
+  results:
+  - task:
+      type: summarization
+      name: Summarization
+    dataset:
+      name: 'SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization'
+      type: samsum
+    metrics:
+    - type: rogue-1
+      value: 43.6283
+      name: Validation ROGUE-1
+    - type: rogue-2
+      value: 19.3096
+      name: Validation ROGUE-2
+    - type: rogue-l
+      value: 41.2140
+      name: Validation ROGUE-L
+---
+
+# bart-large-cnn-samsum
+
+This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/facebook/bart-large-cnn) on the samsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.755
+- Rouge1: 43.6283
+- Rouge2: 19.3096
+- Rougel: 41.2140
+- Rougelsum: 37.2590
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+```python
+from transformers import pipeline
+summarizer = pipeline("summarization", model="AdamCodd/bart-large-cnn-samsum")
+
+conversation = '''Sugi: I am tired of everything in my life.
+Tommy: What? How happy your life is! I do envy you.
+Sugi: You don't know that I have been overprotected by my mother these years. I am really about to leave the family and spread my wings.
+Tommy: Maybe you are right.                                         
+'''
+summarizer(conversation)
+```
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 3e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 1270
+- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 150
+- num_epochs: 1
+
+### Training results
+
+| key | value |
+| --- | ----- |
+| eval_rouge1 | 43.6283 |
+| eval_rouge2 | 19.3096 |
+| eval_rougeL | 41.2140 |
+| eval_rougeLsum | 37.2590 |
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch lightning 2.0.9
+- Tokenizers 0.13.3