Update README.md

README.md

@@ -41,7 +41,7 @@ datasets:
 # Model description
 This `bert-causation-rating-dr1` model is a fine-tuned [biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) model on a small set of manually annotated texts with causation labels. This model is tasked with classifying a sentence into different levels of strength of causation expressed in this sentence.
 
-This `dr1` version is tuned on the set of sentences rated by Rater 1. 
+The sentences in the dataset were rated independently by two researchers. This `dr1` version is tuned on the set of sentences with labels rated by Rater 1. 
 
 # Intended use and limitations
 
@@ -69,7 +69,7 @@ This performance is achieved with the following hyperparameters:
  * Weight decay: 0.111616
  * Warmup ratio: 0.301057
  * Power of polynomial learning rate scheduler: 2.619975
- * Power to the distance measure used in the loss function $\alpha$: 2.0
+ * Power to the distance measure used in the loss function \alpha: 2.0
 
  
 ## Hyperparameter tuning metrics
@@ -82,13 +82,13 @@ The following training configurations apply:
  * `batch_size`: 128
  * `epoch`: 8
  * `max_length` in `torch.utils.data.Dataset`: 128
- * Loss function: the [OLL loss](https://aclanthology.org/2022.coling-1.407/) with a tunable hyperparameter $\alpha$ (Power to the distance measure used in the loss function).
+ * Loss function: the [OLL loss](https://aclanthology.org/2022.coling-1.407/) with a tunable hyperparameter \alpha (Power to the distance measure used in the loss function).
  * `lr`: 7.94278e-05
  * `weight_decay`: 0.111616
  * `warmup_ratio`: 0.301057
  * `lr_scheduler_type`: polynomial
  * `lr_scheduler_kwargs`: `{"power": 2.619975, "lr_end": 1e-8}`
- * Power to the distance measure used in the loss function $\alpha$: 2.0
+ * Power to the distance measure used in the loss function \alpha: 2.0
 
 # Framework versions and devices