*BCER is a lie: *

(B)CER is unrealistic measure of accuracy. I*t is a lie. * I have said it a 
couple of times already. The BCER we get during the training is nowhere 
close to the reality of the accuracy of our model. I have many occasions 
where my training achieved 0 error rate and stopped the training. But, when 
I tested the output using independent evaluation tools, the best I can get 
was 95-97% accuracy on the synthetic data and 90-92% accuracy on actual 
scanned documents (data). 
- So, we need to find a way to turn off the target_error-rate parameter 
which stops the training when the model thinks it achieved 0% error. May be 
can assign a negative value to it. I am going to try it if it will turn it 
off. 
On Tuesday, October 24, 2023 at 3:55:54 PM UTC+3 Des Bw wrote:

> You can add  *training >> data/lang.log &* to the end of your training 
> script (shell) to get a log saved inside your data folder. You also add 
> *DEBUG_INTERVAL=-1 
> training >> data/lang.log &. *This one flashes more detailed information 
> on the console; and saves a short log inside the data folder. If you want 
> to save everything displayed in the console saved to log file, you can 
> check out methods listed here: 
>
> https://unix.stackexchange.com/questions/200637/save-all-the-terminal-output-to-a-file
>
>
> On Tuesday, October 24, 2023 at 3:45:23 PM UTC+3 [email protected] wrote:
>
>> I have made a first try for a fine tuning, the script run a second and 
>> end without any error message. Where can I find a log file ? 
>>
>> Le lun. 23 oct. 2023 à 14:01, Keith Smith <[email protected]> a 
>> écrit :
>>
>>> Rene, the name “foo” is simply an example (or fictitious) font or 
>>> language name.  When training a new language or font, you should replace 
>>> “foo” with the name of your language or font.  The standard is to choose 3 
>>> letters, but that is not required.  In fact, I have been training a font 
>>> named “micr_e13b” and it is working technically for me (though the accuracy 
>>> isn’t good enough yet).  Note the underscore character between sections of 
>>> the name.
>>>
>>>  
>>>
>>> Internal
>>>
>>> *From: *[email protected] <[email protected]> on 
>>> behalf of René JM Clais <[email protected]>
>>> *Date: *Sunday, October 22, 2023 at 12:41 PM
>>> *To: *[email protected] <[email protected]>
>>> *Subject: *[EXTERNAL] Re: [tesseract-ocr] Lessons, best practices, 
>>> recommendations, strategies, hacks
>>>
>>> *CAUTION EXTERNAL EMAIL *
>>> *DO NOT open attachments or click on links from unknown senders or 
>>> unexpected emails.*
>>>
>>>  
>>>
>>> Hi Keith,
>>>
>>> The foo.traindedata is not existing but do you mean : the trainedata I 
>>> want to train   ex:  hye.traineddata  ?
>>>
>>> In my case I should add a new character in the hye.traineddata
>>>
>>> It seems that I can do this using the option 2 !
>>>
>>> But how ?  Which command  should I use to execute this function and what 
>>> does mean this process ?
>>>
>>>  
>>>
>>> Thank you for your help
>>>
>>> Regards
>>>
>>> René
>>>
>>>  
>>>
>>> Le sam. 21 oct. 2023 à 17:18, Keith Smith <[email protected]> a 
>>> écrit :
>>>
>>> Thank you Des for your help in this community.  It is greatly 
>>> appreciated!
>>>
>>> As one who is struggling, may I make a suggestion.
>>>
>>> I have started a google doc here 
>>> <https://urldefense.com/v3/__https://docs.google.com/document/d/1Vz6y4LcqczAAE2yKc_xYecy1eChjHZbsxb13_7ntUh0/edit?usp=sharing__;!!MjXRb4uW6x5k!HFOAD-quUbb2dHADKsKiyk_BK3xW49ZAh87HZ3mPU9myi2Zk2t-bdP3ptvhcsV64KhX43EgYbPFZJ5M8Lr1zVHA$>
>>>  
>>> with a suggested format for a tutorial which would be very helpful to me 
>>> and I think to others. It is editable by anyone with the link.
>>>
>>> I'm glad to put in any work myself, but my guess is that there are 
>>> things in the doc that could be filled without much effort by you or others.
>>>
>>> If this is true, once the doc is filled out, the contents of the google 
>>> doc could be submitted as a PR to the tesstrain repo.
>>>
>>> Again, just a suggestion that I hope would be helpful to all.
>>>
>>>
>>>
>>> Thanks,
>>>
>>> Keith
>>>
>>>  
>>>
>>> On Sat, Oct 21, 2023 at 8:28 AM Des Bw <[email protected]> wrote:
>>>
>>> There is no exhaustive user manual for training tesseract. We all start 
>>> in the darkness; and accumulate bits of information in different places to 
>>> learn the ins and outs of tesseract. 
>>>
>>>  
>>>
>>> It would be great if we can collectively write a better manual. Up until 
>>> then, we can drop /collect our observations, best  practices, hacks and 
>>> lessons we accumulated in our adventure with tesseract.  
>>>
>>>  
>>>
>>> I will start with some of my observations. I collect them by reading in 
>>> between the lines: from my own failed experiments: 
>>>
>>> 1. Training from scratch is very difficult because tesseract requires 
>>> extensive data set. It looks like it requires over 300,000 test lines 
>>> (around 26mb text file).
>>>
>>> https://github.com/tesseract-ocr/tesseract/issues/3909 
>>> <https://urldefense.com/v3/__https://github.com/tesseract-ocr/tesseract/issues/3909__;!!MjXRb4uW6x5k!HFOAD-quUbb2dHADKsKiyk_BK3xW49ZAh87HZ3mPU9myi2Zk2t-bdP3ptvhcsV64KhX43EgYbPFZJ5M8Yk4Xcmo$>
>>>
>>>  
>>>
>>>  Multiple that with the fonts you want to train, the data grows 
>>> exponentially. That requires very powerful computers running for weeks and 
>>> months. 
>>>
>>> So, for the regular users, training from a network layer, or fine tuning 
>>> are the most plausible options. 
>>>
>>>  
>>>
>>> 2. Best practice: make your text lines not too long. The recommended 
>>> number of works in a line is 10-12. Again from the above link. 
>>>
>>>  
>>>
>>> ( ...to be continued)
>>>
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