## `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 |

{"language": "en", "license": "apache-2.0", "tags": ["sagemaker", "bart", "summarization"], "datasets": ["samsum"], "widget": [{"text": "Sugi: I am tired of everything in my life. \nTommy: What? How happy you life is! I do envy you.\nSugi: 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.\nTommy: Maybe you are right. "}], "model-index": [{"name": "bart-large-cnn-samsum", "results": [{"task": {"type": "abstractive-text-summarization", "name": "Abstractive Text Summarization"}, "dataset": {"name": "SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization", "type": "samsum"}, "metrics": [{"type": "rogue-1", "value": 43.2111, "name": "Validation ROGUE-1"}, {"type": "rogue-2", "value": 22.3519, "name": "Validation ROGUE-2"}, {"type": "rogue-l", "value": 33.315, "name": "Validation ROGUE-L"}, {"type": "rogue-1", "value": 41.8283, "name": "Test ROGUE-1"}, {"type": "rogue-2", "value": 20.9857, "name": "Test ROGUE-2"}, {"type": "rogue-l", "value": 32.3602, "name": "Test ROGUE-L"}]}]}]}
transformers pytorch bart text2text-generation sagemaker summarization en dataset:samsum license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bart #text2text-generation #sagemaker #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

'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
* Example Notebooks
* Amazon SageMaker documentation for Hugging Face
* Python SDK SageMaker documentation for Hugging Face
* Deep Learning Container


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
-------




TAGS
#transformers #pytorch #bart #text2text-generation #sagemaker #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #bart #text2text-generation #sagemaker #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
