Fix copied scores

Accidentally copied the POS tagging scores, not the UAS
ljvmiranda921 · Jul 18, 2023 · 192593b · 192593b
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commit 192593b
Showing 1 changed file with 3 additions and 3 deletions.
diff --git a/projects/_posts/2023-08-07-calamancy.md b/projects/_posts/2023-08-07-calamancy.md
@@ -145,9 +145,9 @@ We also evaluated cross-lingual and multilingual approaches in our benchmarks:
 
 | Language Pipeline      | Binary textcat (Hatespeech) | Multilabel textcat (Dengue)  | NER (TLUnified-NER)  | Dependency parsing, UAS (Merged UD) | Dependency parsing, LAS (Merged UD) |
 |------------------------|---------------------------------------------------------|----------------------------------------------------------|-----------------------------------------------------|-------------------------------------|-------------------------------------|
-| uk_core_news_trf       | $$75.24 (0.05)$$                                            | $$65.57 (0.01)$$                                             | $$51.11 (0.02)$$                                        | $$54.77$$                               | $$82.86$$                               |
-| ro_core_news_lg        | $$69.01 (0.01)$$                                            | $$59.10 (0.01)$$                                             | $$02.01 (0.00)$$                                        | $$84.65$$                               | $$82.80$$                               |
-| ca_core_news_trf       | $$70.01 (0.02)$$                                            | $$59.42 (0.03)$$                                             | $$14.58 (0.02)$$                                        | $$91.17$$                               | $$83.09$$                               |
+| uk_core_news_trf       | $$75.24 (0.05)$$                                            | $$65.57 (0.01)$$                                             | $$51.11 (0.02)$$                                        | $$54.77$$                               | $$37.68$$                               |
+| ro_core_news_lg        | $$69.01 (0.01)$$                                            | $$59.10 (0.01)$$                                             | $$02.01 (0.00)$$                                        | $$84.65$$                               | $$65.30$$                               |
+| ca_core_news_trf       | $$70.01 (0.02)$$                                            | $$59.42 (0.03)$$                                             | $$14.58 (0.02)$$                                        | $$91.17$$                               | $$79.30$$                               |
 
 - **Multilingual**: we used XLM RoBERTa and an uncased version of mBERT as our base transformer models. We also finetuned each model for each task and did similar evaluations.
   Note that finetuning on XLM RoBERTa (both base and large versions) may require at least a V100 GPU. I've seen more consistent and stable training with an A100 GPU. Same can be said for mBERT.