Update README.md

README.md

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 # Model Card for Model ID
 
-ModernBERT multi-task fine-tuned on tasksource NLI tasks, including MNLI, ANLI, SICK, WANLI, doc-nli, LingNLI, FOLIO, FOL-NLI, LogicNLI, Label-NLI and all datasets in the below table).
+This model is ModernBERT multi-task fine-tuned on tasksource NLI tasks, including MNLI, ANLI, SICK, WANLI, doc-nli, LingNLI, FOLIO, FOL-NLI, LogicNLI, Label-NLI and all datasets in the below table).
 This is the equivalent of an "instruct" version.
 The model was trained for 200k steps on an Nvidia A30 GPU.
 
 It is very good at reasoning tasks (better than llama 3.1 8B Instruct on ANLI and FOLIO), long context reasoning, sentiment analysis and zero-shot classification with new labels. 
 
-The following table shows model test accuracy. It is the accuracy of the same single transformer with different classification heads on top.
+The following table shows model test accuracy. These are the scores for the same single transformer with different classification heads on top.
 Further gains can be obtained by fine-tuning on a single-task, e.g. SST, but it this checkpoint is great for zero-shot classification and natural language inference (contradiction/entailment/neutral classification).
 
 | test_name                             |   test_accuracy |