Create README.md

README.md

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+
+---
+language: en
+tags:
+- sagemaker
+- bart
+- summarization
+license: apache-2.0
+datasets:
+- samsum
+model-index:
+- name: bart-large-cnn-samsum
+  results:
+  - task: 
+      name: Abstractive Text Summarization
+      type: abstractive-text-summarization
+    dataset:
+      name: "SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization" 
+      type: samsum
+    metrics:
+       - name: Validation ROGUE-1
+         type: rogue-1
+         value: 43.2111
+       - name: Validation ROGUE-2
+         type: rogue-2
+         value: 22.3519
+       - name: Validation ROGUE-L
+         type: rogue-l
+         value: 33.315
+       - name: Test ROGUE-1
+         type: rogue-1
+         value: 41.8283
+       - name: Test ROGUE-2
+         type: rogue-2
+         value: 20.9857
+       - name: Test ROGUE-L
+         type: rogue-l
+         value: 32.3602
+widget:
+- text: | 
+    Sugi: I am tired of everything in my life. 
+    Tommy: What? How happy you life is! I do envy you.
+    Sugi: You don't know that I have been over-protected by my mother these years. I am really about to leave the family and spread my wings.
+    Tommy: Maybe you are right. 
+---
+## `bart-large-cnn-samsum`
+This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
+For more information look at:
+- [🤗 Transformers Documentation: Amazon SageMaker](https://huggingface.co/transformers/sagemaker.html)
+- [Example Notebooks](https://github.com/huggingface/notebooks/tree/master/sagemaker)
+- [Amazon SageMaker documentation for Hugging Face](https://docs.aws.amazon.com/sagemaker/latest/dg/hugging-face.html)
+- [Python SDK SageMaker documentation for Hugging Face](https://sagemaker.readthedocs.io/en/stable/frameworks/huggingface/index.html)
+- [Deep Learning Container](https://github.com/aws/deep-learning-containers/blob/master/available_images.md#huggingface-training-containers)
+## Hyperparameters
+    {
+    "dataset_name": "samsum",
+    "do_eval": true,
+    "do_predict": true,
+    "do_train": true,
+    "fp16": true,
+    "learning_rate": 5e-05,
+    "model_name_or_path": "facebook/bart-large-cnn",
+    "num_train_epochs": 3,
+    "output_dir": "/opt/ml/model",
+    "per_device_eval_batch_size": 4,
+    "per_device_train_batch_size": 4,
+    "predict_with_generate": true,
+    "seed": 7
+}
+## Usage
+    from transformers import pipeline
+    summarizer = pipeline("summarization", model="slauw87/bart-large-cnn-samsum")
+    conversation = '''Sugi: I am tired of everything in my life. 
+    Tommy: What? How happy you life is! I do envy you.
+    Sugi: You don't know that I have been over-protected by my mother these years. I am really about to leave the family and spread my wings.
+    Tommy: Maybe you are right.                                           
+    '''
+    nlp(conversation)
+## Results
+| key | value |
+| --- | ----- |
+| eval_rouge1 | 43.2111 |
+| eval_rouge2 | 22.3519 |
+| eval_rougeL | 33.3153 |
+| eval_rougeLsum | 40.0527 |
+| predict_rouge1 | 41.8283 |
+| predict_rouge2 | 20.9857 |
+| predict_rougeL | 32.3602 |
+| predict_rougeLsum | 38.7316 |