Add evaluation results on the inverse-scaling--NeQA config and train split of inverse-scaling/NeQA

Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\
Your model has been evaluated on the inverse-scaling--NeQA config and train split of the [inverse-scaling/NeQA](https://huggingface.co/datasets/inverse-scaling/NeQA) dataset by

@MicPie

, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-eval-inverse-scaling__NeQA-inverse-scaling__NeQA-1e740e-1694759589).\
Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=inverse-scaling/NeQA).\
Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=inverse-scaling/NeQA).

README.md

@@ -6,6 +6,26 @@ tags:
 - opt
 license: other
 commercial: false
+model-index:
+- name: inverse-scaling/opt-66b_eval
+  results:
+  - task:
+      type: zero-shot-classification
+      name: Zero-Shot Text Classification
+    dataset:
+      name: inverse-scaling/NeQA
+      type: inverse-scaling/NeQA
+      config: inverse-scaling--NeQA
+      split: train
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5366666666666666
+      verified: true
+    - name: Loss
+      type: loss
+      value: 0.7120504426956177
+      verified: true
 ---
 
 # OPT : Open Pre-trained Transformer Language Models