link to dataset

README.md

@@ -6,7 +6,7 @@ tags:
 - token classification
 license: 
 datasets:
-- EMBO/sd-panels
+- EMBO/sd-nlp
 metrics:
 -
 ---
@@ -15,7 +15,7 @@ metrics:
 
 ## Model description
 
-This model is a [RoBERTa base model](https://huggingface.co/roberta-base) that was further trained using a masked language modeling task on a compendium of english scientific textual examples from the life sciences using the [BioLang dataset](https://huggingface.co/datasets/EMBO/biolang) and fine-tuned for token classification on the SourceData [sd-panels](https://huggingface.co/datasets/EMBO/sd-panels) dataset to perform Named Entity Recognition of bioentities. 
+This model is a [RoBERTa base model](https://huggingface.co/roberta-base) that was further trained using a masked language modeling task on a compendium of english scientific textual examples from the life sciences using the [BioLang dataset](https://huggingface.co/datasets/EMBO/biolang). It was then fine-tuned for token classification on the SourceData [sd-nlp](https://huggingface.co/datasets/EMBO/sd-nlp) dataset wit the `NER` task to perform Named Entity Recognition of bioentities. 
 
 
 ## Intended uses & limitations
@@ -43,7 +43,7 @@ The model must be used with the `roberta-base` tokenizer.
 
 ## Training data
 
-The model was trained for token classification using the [EMBO/sd-panels dataset](https://huggingface.co/datasets/EMBO/sd-panels) wich includes manually annotated examples.
+The model was trained for token classification using the [EMBO/sd-nlp `NER`](https://huggingface.co/datasets/EMBO/sd-nlp) dataset wich includes manually annotated examples.
 
 ## Training procedure