Add evaluation results on the default config and test split of billsum

Beep 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 [billsum](https://huggingface.co./datasets/billsum) dataset by @Artifact-AI, using the predictions stored [here](https://huggingface.co./datasets/autoevaluate/autoeval-eval-billsum-default-8a9925-2249471725).\
Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co./spaces/autoevaluate/leaderboards?dataset=billsum).\
Evaluate your model on more datasets [here](https://huggingface.co./spaces/autoevaluate/model-evaluator?dataset=billsum).

README.md

@@ -113,6 +113,42 @@ widget:
     medical parole hearing or medical parole release is scheduled for an inmate receiving
     medical parole consideration, regardless of whether the inmate is sentenced either
     determinately or indeterminately.'
+model-index:
+- name: Artifact-AI/led_base_16384_billsum_summarization
+  results:
+  - task:
+      type: summarization
+      name: Summarization
+    dataset:
+      name: billsum
+      type: billsum
+      config: default
+      split: test
+    metrics:
+    - name: ROUGE-1
+      type: rouge
+      value: 47.6721
+      verified: true
+    - name: ROUGE-2
+      type: rouge
+      value: 26.7372
+      verified: true
+    - name: ROUGE-L
+      type: rouge
+      value: 34.5681
+      verified: true
+    - name: ROUGE-LSUM
+      type: rouge
+      value: 41.5295
+      verified: true
+    - name: loss
+      type: loss
+      value: 2.079916000366211
+      verified: true
+    - name: gen_len
+      type: gen_len
+      value: 128.8152
+      verified: true
 ---
 
 # Longformer Encoder-Decoder (LED) fine-tuned on Billsum