Dear shree, am having a problem training the model, When I added more
samples ... the result got worse, is there a best practice to add training
data to train the model ?

Regards

On Thu, Jul 11, 2019 at 3:15 PM fady taher <fadytahe...@gmail.com> wrote:

> so ... I added  "Cr⁶⁺"  66 times but am getting "Cr³+" instead ... should
> I increase the training data with more samples ??
>
> On Wed, Jul 10, 2019 at 4:56 PM Shree Devi Kumar <shreesh...@gmail.com>
> wrote:
>
>> No. It just means that you have ~25 (136-111) more characters in your new
>> unicharset that you are training on.
>>
>> *given outputs 111 not equal to unicharset of 136.*
>>
>>
>>
>> On Wed, Jul 10, 2019 at 8:01 PM fady taher <fadytahe...@gmail.com> wrote:
>>
>>> should I worry regarding the below error ?
>>>
>>> Warning: LSTMTrainer deserialized an LSTMRecognizer!
>>> Continuing from ../tesstutorial/eng_layer_eng/eng.lstm
>>> *Appending a new network to an old one!!Warning: given outputs 111 not
>>> equal to unicharset of 136.*
>>> Num outputs,weights in Series:
>>>   Lfx256:256, 361472
>>>   Fc136:136, 34952
>>> Total weights = 396424
>>> Built network:[1,36,0,1[C3,3Ft16]Mp3,3Lfys64Lfx96Lrx96Lfx256Fc136] from
>>> request [Lfx256 O1c111]
>>> Training parameters:
>>>   Debug interval = 0, weights = 0.1, learning rate = 0.001, momentum=0.5
>>> null char=135
>>>
>>> On Tue, Jul 9, 2019 at 1:41 PM fady taher <fadytahe...@gmail.com> wrote:
>>>
>>>> will try and feed you back, thanks alot
>>>>
>>>> On Tue, Jul 9, 2019 at 1:40 PM Shree Devi Kumar <shreesh...@gmail.com>
>>>> wrote:
>>>>
>>>>> I don't think I had any (or enough) plus superscript in my
>>>>> training_text.
>>>>>
>>>>> Treat this as an example and train as per the data you expect.
>>>>>
>>>>> On Tue, 9 Jul 2019, 17:01 fady taher, <fadytahe...@gmail.com> wrote:
>>>>>
>>>>>> Dear Shree, thanks for you quick response ... I gave a try to the
>>>>>> submodule ... it gave results to *Cr⁶⁶ *while it should have been *Cr
>>>>>> *⁶*⁺ *any ideas if this is solvable *?*
>>>>>>
>>>>>>
>>>>>> Regards
>>>>>>
>>>>>> On Tue, Jul 9, 2019 at 1:14 PM Shree Devi Kumar <shreesh...@gmail.com>
>>>>>> wrote:
>>>>>>
>>>>>>> If you use the submodule you will save time taken in running the
>>>>>>> 8-makedata_layernew.sh script. However, if you have modified
>>>>>>> training_text or want to checkout the full process, run the script.
>>>>>>>
>>>>>>> On Tue, Jul 9, 2019 at 4:33 PM fady taher <fadytahe...@gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> I can see that you have mentioned
>>>>>>>>>
>>>>>>>> "IT IS NOT REQUIRED TO RUN THIS SCRIPT AS THE OUTPUT FOLDERS ARE
>>>>>>>> PROVIDED AS A SUBMODULE IN THE REPO. Use git submodule update --init to
>>>>>>>> download the files (approx 600MB)."
>>>>>>>> so, should I just use the eng.traineddata found in tessdata folder ?
>>>>>>>>
>>>>>>>>
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>>
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>> ____________________________________________________________
>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com
>>
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