README.md

@@ -1,93 +1,53 @@
+
 ---
 language: en
-license: mit
 tags:
 - sagemaker
 - bart
 - summarization
+license: apache-2.0
 datasets:
 - samsum
-widget:
-- text: "Jeff: Can I train a \U0001F917 Transformers model on Amazon SageMaker? \n\
-    Philipp: Sure you can use the new Hugging Face Deep Learning Container. \nJeff:\
-    \ ok.\nJeff: and how can I get started? \nJeff: where can I find documentation?\
-    \ \nPhilipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face\n"
 model-index:
 - name: bart-large-cnn-samsum
   results:
-  - task:
+  - task: 
-      type: summarization
+      name: Abstractive Text Summarization
-      name: Summarization
+      type: abstractive-text-summarization
     dataset:
-      name: 'SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization'
+      name: SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization 
       type: samsum
     metrics:
-    - type: rogue-1
+       - name: Validation ROGUE-1
-      value: 42.621
+         type: rogue-1
-      name: Validation ROGUE-1
+         value: 42.621
-    - type: rogue-2
+       - name: Validation ROGUE-2
-      value: 21.9825
+         type: rogue-2
-      name: Validation ROGUE-2
+         value: 21.9825
-    - type: rogue-l
+       - name: Validation ROGUE-L
-      value: 33.034
+         type: rogue-l
-      name: Validation ROGUE-L
+         value: 33.034
-    - type: rogue-1
+       - name: Test ROGUE-1
-      value: 41.3174
+         type: rogue-1
-      name: Test ROGUE-1
+         value: 41.3174
-    - type: rogue-2
+       - name: Test ROGUE-2
-      value: 20.8716
+         type: rogue-2
-      name: Test ROGUE-2
+         value: 20.8716
-    - type: rogue-l
+       - name: Test ROGUE-L
-      value: 32.1337
+         type: rogue-l
-      name: Test ROGUE-L
+         value: 32.1337
-  - task:
+widget:
-      type: summarization
+- text: | 
-      name: Summarization
+    Jeff: Can I train a 🤗 Transformers model on Amazon SageMaker? 
-    dataset:
+    Philipp: Sure you can use the new Hugging Face Deep Learning Container. 
-      name: samsum
+    Jeff: ok.
-      type: samsum
+    Jeff: and how can I get started? 
-      config: samsum
+    Jeff: where can I find documentation? 
-      split: test
+    Philipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face 
-    metrics:
-    - type: rouge
-      value: 41.3282
-      name: ROUGE-1
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTYzNzZkZDUzOWQzNGYxYTJhNGE4YWYyZjA0NzMyOWUzMDNhMmVhYzY1YTM0ZTJhYjliNGE4MDZhMjhhYjRkYSIsInZlcnNpb24iOjF9.OOM6l3v5rJCndmUIJV-2SDh2NjbPo5IgQOSL-Ju1Gwbi1voL5amsDEDOelaqlUBE3n55KkUsMLZhyn66yWxZBQ
-    - type: rouge
-      value: 20.8755
-      name: ROUGE-2
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWZiODFiYWQzY2NmOTc5YjA3NTI0YzQ1MzQ0ODk2NjgyMmVlMjA5MjZiNTJkMGRmZGEzN2M3MDNkMjkxMDVhYSIsInZlcnNpb24iOjF9.b8cPk2-IL24La3Vd0hhtii4tRXujh5urAwy6IVeTWHwYfXaURyC2CcQOWtlOx5bdO5KACeaJFrFBCGgjk-VGCQ
-    - type: rouge
-      value: 32.1353
-      name: ROUGE-L
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWNmYzdiYWQ2ZWRkYzRiMGMxNWUwODgwZTdkY2NjZTc1NWE5NTFiMzU0OTU1N2JjN2ExYWQ2NGZkNjk5OTc4YSIsInZlcnNpb24iOjF9.Fzv4p-TEVicljiCqsBJHK1GsnE_AwGqamVmxTPI0WBNSIhZEhliRGmIL_z1pDq6WOzv3GN2YUGvhowU7GxnyAQ
-    - type: rouge
-      value: 38.401
-      name: ROUGE-LSUM
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGI4MWY0NWMxMmQ0ODQ5MDhiNDczMDAzYzJkODBiMzgzYWNkMWM2YTZkZDJmNWJiOGQ3MmNjMGViN2UzYWI2ZSIsInZlcnNpb24iOjF9.7lw3h5k5lJ7tYFLZGUtLyDabFYd00l6ByhmvkW4fykocBy9Blyin4tdw4Xps4DW-pmrdMLgidHxBWz5MrSx1Bw
-    - type: loss
-      value: 1.4297215938568115
-      name: loss
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzI0ZWNhNDM5YTViZDMyZGJjMDA1ZWFjYzNhOTdlOTFiNzhhMDBjNmM2MjA3ZmRkZjJjMjEyMGY3MzcwOTI2NyIsInZlcnNpb24iOjF9.oNaZsAtUDqGAqoZWJavlcW7PKx1AWsnkbhaQxadpOKk_u7ywJJabvTtzyx_DwEgZslgDETCf4MM-JKitZKjiDA
-    - type: gen_len
-      value: 60.0757
-      name: gen_len
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTgwYWYwMDRkNTJkMDM5N2I2MWNmYzQ3OWM1NDJmODUyZGViMGE4ZTdkNmIwYWM2N2VjZDNmN2RiMDE4YTYyYiIsInZlcnNpb24iOjF9.PbXTcNYX_SW-BuRQEcqyc21M7uKrOMbffQSAK6k2GLzTVRrzZxsDC57ktKL68zRY8fSiRGsnknOwv-nAR6YBCQ
 ---
 
 ## `bart-large-cnn-samsum`
 
-> If you want to use the model you should try a newer fine-tuned FLAN-T5 version [philschmid/flan-t5-base-samsum](https://huggingface.co/philschmid/flan-t5-base-samsum) out socring the BART version with `+6` on `ROGUE1` achieving `47.24`.
-
-# TRY [philschmid/flan-t5-base-samsum](https://huggingface.co/philschmid/flan-t5-base-samsum)
-
-
 This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
 
 For more information look at:
@@ -128,7 +88,7 @@ Jeff: and how can I get started?
 Jeff: where can I find documentation? 
 Philipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face                                           
 '''
-summarizer(conversation)
+nlp(conversation)
 ```
 
 ## Results