Update README.md

README.md

@@ -1,19 +1,21 @@
 ---
 license: mit
+language: en
 tags:
 - generated_from_trainer
 model-index:
 - name: verdict-classifier-en
-  results: []
+  results:
+  - task:
+      type: text-classification
+      name: Verdict Classification
+widget:
+- "One might think that this is true, but it's taken out of context."
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# verdict-classifier-en
-
-This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
-It achieves the following results on the evaluation set:
+# English Verdict Classifier
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on 2,500 deduplicated verdicts from [Google Fact Check Tools API](https://developers.google.com/fact-check/tools/api/reference/rest/v1alpha1/claims/search), translated into English with the [Google Cloud Translation API](https://cloud.google.com/translate/docs/reference/rest/).
+It achieves the following results on the evaluation set, being 1,000 such verdicts translated into English, but here including duplicates to represent the true distribution:
 - Loss: 0.1304
 - F1 Macro: 0.8868
 - F1 Misinformation: 0.9832
@@ -24,17 +26,6 @@ It achieves the following results on the evaluation set:
 - Prec Factual: 0.9783
 - Prec Other: 0.6038
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
 
 ## Training procedure
 
@@ -90,4 +81,4 @@ The following hyperparameters were used during training:
 - Transformers 4.11.3
 - Pytorch 1.9.0+cu102
 - Datasets 1.9.0
-- Tokenizers 0.10.2
+- Tokenizers 0.10.2