Fixed pseudo F-measure metric in README.md

README.md

@@ -20,11 +20,13 @@ This model is a fine-tuned version of [nvidia/segformer-b3-finetuned-cityscapes-
 It achieves the following results on the evaluation set on DIBCO metrics:
 - loss: 0.1017
 - F-measure: 0.9776
-- probabilistic F-measure: 0.9531
+- pseudo F-measure: 0.9531
 - PSNR: 14.5040
 - DRD: 5.3749
 
-For more information on DIBCO metrics, see the [paper](https://ieeexplore.ieee.org/document/8270159) in which they were introduced.
+where PSNR stands for peak signal-to-noise ratio and DND for distance reciprocal distortion.
+
+For more information on DIBCO metrics, see the 2017 introductory [paper](https://ieeexplore.ieee.org/document/8270159).
 
 **Warning:** This model only accepts images with a resolution of 640 due to compute constraints on Colab free tier during training.
 
@@ -58,7 +60,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| training loss | epoch | step | validation loss | F-measure | probabilistic F-measure | PSNR    | DRD      |
+| training loss | epoch | step | validation loss | F-measure | pseudo F-measure | PSNR    | DRD      |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:-------:|:--------:|
 | 0.6667        | 1.03  | 10   | 0.6683          | 0.7127   | 0.6831    | 4.8248  | 107.2894 |
 | 0.6371        | 2.05  | 20   | 0.6390          | 0.8173   | 0.7360    | 6.1079  | 69.7770  |