OmkarPathak
Extract Info
Hi @OmkarPathak @dazzag24 , I had clone your data and started parsing the resume but i found some difficulty in extracting the experience and company names can you tell how it works from utils.py file from the functions extract_experience and extract_competencies and actually for parsing i had given my resume in that i mentioned as experience and company as side headings but also i was unable to get it
Thanks and Regards, Manikantha Sekhar
@mady143 yes it is very difficult to parse experience and company names. The model that we have trained is not yet accurate in extracting these entities. If you want, you can train your model and then try the same
@OmkarPathak okay how to train the model is their any training process in existing code and also i was unable to print the data from the some other functions which are in different files only getting the prints from views.py can you explain me y?
Thanks and Regards, Manikantha Sekhar
@mady143
okay how to train the model
There are these two files: train and test. Your training data should be in the format like this
also i was unable to print the data from the some other functions which are in different files only getting the prints from views.py can you explain me y?
can you elaborate this issue?
Hi @OmkarPathak , I had done training process like , (my_resume_pyresparser) manikantha@Manikantha-PC:~/Downloads/pyresparser/pyresparser$ python custom_train.py Created blank 'en' model Creating new pipe Starting iteration 0 Losses {'ner': 83948.83401187272} Starting iteration 1 Losses {'ner': 50266.19444030836} Starting iteration 2 Losses {'ner': 43155.15530648954} Starting iteration 3 Losses {'ner': 40022.855776749966} Starting iteration 4 Losses {'ner': 34466.00632723602} Starting iteration 5 Losses {'ner': 34260.82662641417} Starting iteration 6 Losses {'ner': 32415.686345038288} Starting iteration 7 Losses {'ner': 30070.207913930943} Starting iteration 8 Losses {'ner': 28438.445806700598} Starting iteration 9 Losses {'ner': 28697.96626680234} Starting iteration 10 Losses {'ner': 24849.52654336362} Starting iteration 11 Losses {'ner': 25142.6057196642} Starting iteration 12 Losses {'ner': 24079.14422368379} Starting iteration 13 Losses {'ner': 24257.180968177847} Starting iteration 14 Losses {'ner': 23090.409918362162} Starting iteration 15 Losses {'ner': 23996.485883846104} Starting iteration 16 Losses {'ner': 23423.123708186868} Starting iteration 17 Losses {'ner': 20781.21235375348} Starting iteration 18 Losses {'ner': 20025.49499945144} Starting iteration 19 Losses {'ner': 19859.159115096158} Starting iteration 20 Losses {'ner': 19835.303925276472} Starting iteration 21 Losses {'ner': 17874.102371228983} Starting iteration 22 Losses {'ner': 18699.1655548761} Starting iteration 23 Losses {'ner': 18402.408249338278} Starting iteration 24 Losses {'ner': 17600.381271163213} Starting iteration 25 Losses {'ner': 17745.068060417587} Starting iteration 26 Losses {'ner': 17847.67826112547} Starting iteration 27 Losses {'ner': 16500.602022483115} Starting iteration 28 Losses {'ner': 17123.114352572746} Starting iteration 29 Losses {'ner': 17659.68112649223} Entities in 'Marathwada Mitra Mandals College of Engineering' Name Marathwada Mitra Mandals College of Engineering Saved model to /home/manikantha/Downloads/pyresparser/pyresparser Loading from /home/manikantha/Downloads/pyresparser/pyresparser Name Marathwada Mitra Mandals College of Engineering and later i run custom_t.py as (my_resume_pyresparser) manikantha@Manikantha-PC:~/Downloads/pyresparser/pyresparser$ python custom_t.py i am getting {} empty dict so can you tell me how to resolve the issue...
Thanks and Regards, Manikantha Sekhar..
Hi @OmkarPathak actually i used pyresparser to extract the Resume and get the data from that though i am getting the all required data like name, email, mobile_number, education(degree) designation, and skills but in this also missing the experience so how can i get the experience can you explain me
Thanks and Regrads, Manikantha Sekhar...
Hi @OmkarPathak , I had done training process like , (my_resume_pyresparser) manikantha@Manikantha-PC:~/Downloads/pyresparser/pyresparser$ python custom_train.py Created blank 'en' model Creating new pipe Starting iteration 0 Losses {'ner': 83948.83401187272} Starting iteration 1 Losses {'ner': 50266.19444030836} Starting iteration 2 Losses {'ner': 43155.15530648954} Starting iteration 3 Losses {'ner': 40022.855776749966} Starting iteration 4 Losses {'ner': 34466.00632723602} Starting iteration 5 Losses {'ner': 34260.82662641417} Starting iteration 6 Losses {'ner': 32415.686345038288} Starting iteration 7 Losses {'ner': 30070.207913930943} Starting iteration 8 Losses {'ner': 28438.445806700598} Starting iteration 9 Losses {'ner': 28697.96626680234} Starting iteration 10 Losses {'ner': 24849.52654336362} Starting iteration 11 Losses {'ner': 25142.6057196642} Starting iteration 12 Losses {'ner': 24079.14422368379} Starting iteration 13 Losses {'ner': 24257.180968177847} Starting iteration 14 Losses {'ner': 23090.409918362162} Starting iteration 15 Losses {'ner': 23996.485883846104} Starting iteration 16 Losses {'ner': 23423.123708186868} Starting iteration 17 Losses {'ner': 20781.21235375348} Starting iteration 18 Losses {'ner': 20025.49499945144} Starting iteration 19 Losses {'ner': 19859.159115096158} Starting iteration 20 Losses {'ner': 19835.303925276472} Starting iteration 21 Losses {'ner': 17874.102371228983} Starting iteration 22 Losses {'ner': 18699.1655548761} Starting iteration 23 Losses {'ner': 18402.408249338278} Starting iteration 24 Losses {'ner': 17600.381271163213} Starting iteration 25 Losses {'ner': 17745.068060417587} Starting iteration 26 Losses {'ner': 17847.67826112547} Starting iteration 27 Losses {'ner': 16500.602022483115} Starting iteration 28 Losses {'ner': 17123.114352572746} Starting iteration 29 Losses {'ner': 17659.68112649223} Entities in 'Marathwada Mitra Mandals College of Engineering' Name Marathwada Mitra Mandals College of Engineering Saved model to /home/manikantha/Downloads/pyresparser/pyresparser Loading from /home/manikantha/Downloads/pyresparser/pyresparser Name Marathwada Mitra Mandals College of Engineering and later i run custom_t.py as (my_resume_pyresparser) manikantha@Manikantha-PC:~/Downloads/pyresparser/pyresparser$ python custom_t.py i am getting {} empty dict so can you tell me how to resolve the issue...
Thanks and Regards, Manikantha Sekhar..
I resolved this issue by increasing the iterations so at first i tried for 30 then empty dict as an output and later i was tried for 50 then i got the output a little bit so their is an issue to resolve is increase the iterations
Hi @OmkarPathak , How can i link the train and test to this folder to get the accurate experience of the candidate in the resume and display in the browser
in the above image i have to display the experience also before training and testing i was unable to get the experience so i remove the experience column but now i am running the training and testing files from another github code Pyreparser (https://github.com/OmkarPathak/pyresparser) so i how could i put these files in https://github.com/OmkarPathak/ResumeParser/ in this project
please help me in this
Thanks & Regards, Manikantha Sekhar..
@mady143 you can do it using python setup.py install. This will install pyresparser using your pre-trained model. Make sure you uninstall previously installed version or else install your trained pyresparser into an entirely new environment
@OmkarPathak , https://github.com/OmkarPathak/pyresparser how can i test these code through UI to get the result as like your previous code in https://github.com/OmkarPathak/ResumeParser/ to get the experience and company names....
@mady143 for that you need the knowledge of django. You can add you're fields in views.py and then render them in template
Hi @OmkarPathak , Actually i am developing a module to match the job description we have to get the matched resume and also matches the experience though for that i had used pyresparser package for that in some cases or some resume i am getting the total_experience as 4.7 like that but missing the experience but giving the content with month year its unable to calculate the overall years can you explain in a simple way either with training process or as in normal way can you help me in this or you can given any related links which matches for my requirement...
Thanks and Regards, Manikantha Sekhar...