I see there have been some questions about what 'Epoch 1/10 1656/3125' means during the training of a neural network. I will try to clarify this here.
In the context of neural network training, an 'epoch' corresponds to a complete pass through the training dataset. For example, if you have 1000 images in your training dataset, one epoch would correspond to the network passing over all of these 1000 images.
In the example 'Epoch 1/10 1656/3125', '1/10' means that the network is currently in the first epoch of training, and there will be a total of 10 epochs. So, the training dataset will be passed through the network a total of 10 times.
'1656/3125' indicates the progress of the training during this epoch. '1656' is the current batch number and '3125' is the total number of batches. The batch size is the number of training examples passed through the network at once. For example, if you have a batch size of 32, then 32 training examples would be passed through the network each time. So, if you have 100000 training examples, they would be divided into 3125 batches of 32 examples each (100000 / 32 = 3125).
In summary, 'Epoch 1/10 1656/3125' means that the network is currently being trained on the 1656th batch of the first epoch. There will be a total of 3125 batches in this epoch and a total of 10 epochs during the training.
I hope this clarifies things! If you have any other questions, please feel free to ask.
Best regards,
The image where you see character written are different characters of a language that are separated into several different folders with the language used for training to then identify similarities with the voynich characters also trained.
![[Image: Capture-d-cran-2023-08-31-073921.png]](https://i.ibb.co/6rKNWKj/Capture-d-cran-2023-08-31-073921.png)
![[Image: Capture-d-cran-2023-08-31-074028.png]](https://i.ibb.co/g3dngdz/Capture-d-cran-2023-08-31-074028.png)
In the context of neural network training, an 'epoch' corresponds to a complete pass through the training dataset. For example, if you have 1000 images in your training dataset, one epoch would correspond to the network passing over all of these 1000 images.
In the example 'Epoch 1/10 1656/3125', '1/10' means that the network is currently in the first epoch of training, and there will be a total of 10 epochs. So, the training dataset will be passed through the network a total of 10 times.
'1656/3125' indicates the progress of the training during this epoch. '1656' is the current batch number and '3125' is the total number of batches. The batch size is the number of training examples passed through the network at once. For example, if you have a batch size of 32, then 32 training examples would be passed through the network each time. So, if you have 100000 training examples, they would be divided into 3125 batches of 32 examples each (100000 / 32 = 3125).
In summary, 'Epoch 1/10 1656/3125' means that the network is currently being trained on the 1656th batch of the first epoch. There will be a total of 3125 batches in this epoch and a total of 10 epochs during the training.
I hope this clarifies things! If you have any other questions, please feel free to ask.
Best regards,
The image where you see character written are different characters of a language that are separated into several different folders with the language used for training to then identify similarities with the voynich characters also trained.