On Tue, Aug 21, 2018 at 2:47 PM Jacob Biros <[email protected]>
wrote:

> Thank you for your response.  The command that I posted previously was for
> fine tuning, so I was hoping to figure out what was causing the changes in
> accuracy when changes to the parameters should have no effect at all.j
>
> I'm not sure if we will move forward with replacing the layers, but I will
> post about it if we do.
>
> Thanks again!
>
> On Tue, Aug 21, 2018 at 6:08 PM, Shree Devi Kumar <[email protected]>
> wrote:
>
>> >lstmtraining --model_output ./layer_from_deva/layer --continue_from
>> ./layer_from_deva/Devanagari.lstm --append_index 5 --net_spec '[Lfx192
>> O1c1]' --traineddata ./sanplustrain/san/san.traineddata --train_listfile
>> ./sanplustrain/san.training_files.txt --eval_listfile
>> ./sanpluseval/san.training_files.txt --debug_interval 0 --max_image_MB 6000
>> --max_iterations 500
>> Loaded file ./layer_from_deva/Devanagari.lstm, unpacking...
>> Warning: LSTMTrainer deserialized an LSTMRecognizer!
>> Continuing from ./layer_from_deva/Devanagari.lstm
>> Appending a new network to an old one!!Warning: given outputs 1 not equal
>> to unicharset of 149.
>> Num outputs,weights in Series:
>>   Lfx192:192, 197376
>>   Fc149:149, 28757
>> Total weights = 226133
>> Built network:[1,48,0,1[C3,3Ft16]Mp3,3Lfys64Lfx64Lrx64Lfx192Fc149] from
>> request [Lfx192 O1c1]
>> Training parameters:
>>   Debug interval = 0, weights = 0.1, learning rate = 0.001, momentum=0.5
>>
>>
>> I  have not tried changing the parameters even with replace layers. Do
>> provide feedback on your experience,
>>
>>
>> On Tue, Aug 21, 2018 at 12:00 PM Jacob Biros <[email protected]>
>> wrote:
>>
>>> Thank you for the prompt response!
>>>
>>> On Tue, Aug 21, 2018 at 1:14 PM, Shree Devi Kumar <[email protected]>
>>> wrote:
>>>
>>>> If you want to change parameters, please look at the replace layers
>>>> option. With fine tuning you cannot change them.
>>>>
>>>> On Tue 21 Aug, 2018, 7:27 AM , <[email protected]> wrote:
>>>>
>>>>> Is it possible to change the parameters when Fine Tuning?
>>>>>
>>>>> The documentation says "Fine tuning is the process of training an
>>>>> existing model on new data without changing any part of the network", but
>>>>> does that mean that parameters like momentum, learning rate, etc.  cannot
>>>>> be changed?
>>>>>
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>>
>>
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>>
>> ____________________________________________________________
>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com
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