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Add evaluation results on the default config and test split of xsum
Browse filesBeep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\
Your model has been evaluated on the default config and test split of the [xsum](https://huggingface.co/datasets/xsum) dataset by
@zuzannad1
, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-eval-xsum-default-7c65dc-60294145405).\
Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=xsum).\
Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=xsum).
README.md
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-
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---
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language: en
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tags:
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- sagemaker
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- bart
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- summarization
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license: apache-2.0
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datasets:
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- samsum
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model-index:
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- name: bart-large-cnn-samsum
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results:
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- task:
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name: Abstractive Text Summarization
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type: abstractive-text-summarization
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dataset:
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name:
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type: samsum
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metrics:
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---
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## `bart-large-cnn-samsum`
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This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
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---
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language: en
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+
license: apache-2.0
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tags:
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- sagemaker
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- bart
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- summarization
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datasets:
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- samsum
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+
widget:
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- text: "Sugi: I am tired of everything in my life. \nTommy: What? How happy you life\
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\ is! I do envy you.\nSugi: You don't know that I have been over-protected by\
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\ my mother these years. I am really about to leave the family and spread my wings.\n\
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Tommy: Maybe you are right. "
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model-index:
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- name: bart-large-cnn-samsum
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results:
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+
- task:
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type: abstractive-text-summarization
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name: Abstractive Text Summarization
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dataset:
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name: 'SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization'
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type: samsum
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metrics:
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- type: rogue-1
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value: 43.2111
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name: Validation ROGUE-1
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- type: rogue-2
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value: 22.3519
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name: Validation ROGUE-2
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- type: rogue-l
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value: 33.315
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name: Validation ROGUE-L
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- type: rogue-1
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value: 41.8283
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name: Test ROGUE-1
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- type: rogue-2
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value: 20.9857
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name: Test ROGUE-2
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- type: rogue-l
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value: 32.3602
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name: Test ROGUE-L
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- task:
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type: summarization
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name: Summarization
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dataset:
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name: xsum
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type: xsum
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config: default
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split: test
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metrics:
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- type: rouge
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value: 21.5288
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name: ROUGE-1
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzYyNWVjMjFlYTBhODc5MzU1MjgwZjM4YTlkZmNiOWFhNDhjMDFlMDhkYmIwNWI1MzRmNDM4OWFiN2YyNzc4MyIsInZlcnNpb24iOjF9.jc31m48cpd_2oEqfr_h_N3mJ2EEvyivpNoP_lAeN-QqiJPbT7iWN1RTSzlTMaQjlRTxW3l45-eM9NCbi859eBA
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- type: rouge
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value: 4.3523
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name: ROUGE-2
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjkxYjNiZTgxYzUwYTYzN2JhZTZiZDBhNjU0Mjg3N2EyY2M4ZjY0MDI5MDdmMTRjNDljZDI3NjdjMjdiN2NhMyIsInZlcnNpb24iOjF9.-yLkLjyRddLpQRBYndrrHsS71frqLMOy_waw1JixjsofLVGkpeciRQubOjDGd307pe7TasA_IUJwDIr2BSNfBw
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- type: rouge
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value: 14.2343
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name: ROUGE-L
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGMxOGY3ODFhYmIxYjMzMDEwNWFiZmQ1NTAyYzJmNzRiYmM2YjIzMmRkNGY1ZWJhY2UyZDhkZGMwM2Q1ODNlMyIsInZlcnNpb24iOjF9.nzFPJI_6uZZ_8K_n7qt0_OBiMAZh9chekdGqn9xZ_jrQ-ppNVtFZfPweUnpV5JjDAGIzmrxBIi8Y7ci8M13SAA
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- type: rouge
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value: 17.3884
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name: ROUGE-LSUM
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWVkMjU3MjAwNzM3MjQ1ZGZiN2RhNGRjNDBlMGE2YTU2NDdjOWU2MDc2NDg0MmI5YTY0NjI4NDc0NTBjZGUzMSIsInZlcnNpb24iOjF9.W4TUCxCvddu21StnHsdwBuNIPB8mBqNVRgSOCg0LNNQoCXFI0eOobUIuYGuliYpka3rBEK2BQC4km7yad-vxAw
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- type: loss
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value: 2.78153133392334
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name: loss
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjI4NTk3NWE3YTM0MTZiY2VkYmNhZWU5NWZlZDQ2ZjUxMWM2Y2FiMTk1Y2JmYzBmMmQxMTcxNGRmZWM5ZDM0ZSIsInZlcnNpb24iOjF9.m5UmARkSVyshaDZehFexQgGfUnrZuGvF19MJUjURe7iJlWjpeN8hYtoaa9ym3_0Yc8qykrsTkEIVlM-ft5SjDQ
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- type: gen_len
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value: 73.6503
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name: gen_len
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verified: true
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTM5MDYzOWJiZTc0ZThmNDAzODA4NDZmMWY5N2JjZWJiOTkzM2Y3MGZkOWU3NGM4MzdkYjI2ZDQ2ZTg3MWMwMiIsInZlcnNpb24iOjF9.Zy82pW8bQHuFcGxDkzNMt4brNUcY4m18tRHieISKVQ77Z7UymFzJ19yW_2MP-ONJv6X2zkTsyUoZDhZ3OYSeBw
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---
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## `bart-large-cnn-samsum`
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This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
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