Update README.md

README.md

@@ -22,7 +22,7 @@ CLIP_TROHN-Img_Detector is a model presented in the [BiVLC](https://github.com/I
 * Optimizer: Adam optimizer with beta1 = 0.9, beta2 = 0.999, eps = 1e-08 and without weight decay.
 * Loss function: Binary cross-entropy loss (BCELoss).
 * Batch size: We define a batch size of 400.
-* Epochs: We trained the text detector over 10 epochs and the image detectors over 1 epoch. We used validation accuracy as the model selection criterion, i.e. we selected the model with highest accuracy in the corresponding validation set.
+* Epochs: We trained the text detector over 10 epochs and the image detector over 1 epoch. We used validation accuracy as the model selection criterion, i.e. we selected the model with highest accuracy in the corresponding validation set.
 * Data: Then sigmoid neuron is trained with [TROHN-Img](https://huggingface.co/datasets/imirandam/TROHN-Img) dataset.
 
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