Create README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+- seq2seq
+- summarization
+datasets:
+- samsum
+metrics:
+- rouge
+widget:
+- text: >
+    Emily: Hey Alex, have you heard about the new restaurant that opened
+    downtown?
+
+    Alex: No, I haven't. What's it called?
+
+    Emily: It's called "Savory Bites." They say it has the best pasta in town.
+
+    Alex: That sounds delicious. When are you thinking of checking it out?
+
+    Emily: How about this Saturday? We can make it a dinner date.
+
+    Alex: Sounds like a plan, Emily. I'm looking forward to it.
+model-index:
+- name: bart-large-xsum-samsum
+  results:
+  - task:
+      type: summarization
+      name: Summarization
+    dataset:
+      name: >-
+        SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive
+        Summarization
+      type: samsum
+    metrics:
+    - type: rouge-1
+      value: 54.3073
+      name: Validation ROUGE-1
+    - type: rouge-2
+      value: 29.0947
+      name: Validation ROUGE-2
+    - type: rouge-l
+      value: 44.4676
+      name: Validation ROUGE-L
+---
+
+# bart-large-cnn-samsum
+
+This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the [samsum dataset](https://huggingface.co/datasets/samsum).
+It achieves the following results on the evaluation set:
+- Loss: 0.759
+- Rouge1: 54.3073
+- Rouge2: 29.0947
+- Rougel: 44.4676
+- Rougelsum: 49.895
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+```python
+from transformers import pipeline
+summarizer = pipeline("summarization", model="AdamCodd/bart-large-cnn-samsum")
+
+conversation = '''Emily: Hey Alex, have you heard about the new restaurant that opened downtown?
+Alex: No, I haven't. What's it called?
+Emily: It's called "Savory Bites." They say it has the best pasta in town.
+Alex: That sounds delicious. When are you thinking of checking it out?
+Emily: How about this Saturday? We can make it a dinner date.
+Alex: Sounds like a plan, Emily. I'm looking forward to it.                                       
+'''
+result = summarizer(conversation)
+print(result)
+```
+
+## 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 | 54.3073 |
+| eval_rouge2 | 29.0947 |
+| eval_rougeL | 44.4676 |
+| eval_rougeLsum | 49.895 |
+
+### Framework versions
+
+- Transformers 4.35.0
+- Accelerate 0.24.1
+- Datasets 2.14.6
+- Tokenizers 0.14.3
+
+If you want to support me, you can [here](https://ko-fi.com/adamcodd).