Comments (4)
The code is data agnostic: if you provide the right vocab files / data files, it will be able to learn any task.
from tf_ner.
@guillaumegenthial Hi, I used some tags other than PER, LOC, ORG &MISC,but when I used conlleval to evaluate the predictions, it only has accuray not zero, precision,recall and FB1 are all zeros, and there isn't evaluation results for each tag. The output of conlleval is as follows, can you tell me what's wrong? Thank you~
processed 120652 tokens with 0 phrases; found: 0 phrases; correct: 0.
accuracy: 97.37%; precision: 0.00%; recall: 0.00%; FB1: 0.00
from tf_ner.
@guillaumegenthial Hi, I used some tags other than PER, LOC, ORG &MISC,but when I used conlleval to evaluate the predictions, it only has accuray not zero, precision,recall and FB1 are all zeros, and there isn't evaluation results for each tag. The output of conlleval is as follows, can you tell me what's wrong? Thank you~
processed 120652 tokens with 0 phrases; found: 0 phrases; correct: 0.
accuracy: 97.37%; precision: 0.00%; recall: 0.00%; FB1: 0.00
Face same problem ? Did you able to resolve this problem
from tf_ner.
I think you need to provide -r inorder get the result for raw tags. below are the options
conlleval: evaluate result of processing CoNLL-2000 shared task
usage: conlleval [-l] [-r] [-d delimiterTag] [-o oTag] < file
README: http://cnts.uia.ac.be/conll2000/chunking/output.html
options: l: generate LaTeX output for tables like in
http://cnts.uia.ac.be/conll2003/ner/example.tex
r: accept raw result tags (without B- and I- prefix;
assumes one word per chunk)
d: alternative delimiter tag (default is single space)
o: alternative outside tag (default is O)
note: the file should contain lines with items separated
by $delimiter characters (default space). The final
two items should contain the correct tag and the
guessed tag in that order. Sentences should be
separated from each other by empty lines or lines
with $boundary fields (default -X-).
url: http://lcg-www.uia.ac.be/conll2000/chunking/
started: 1998-09-25
version: 2004-01-26
author: Erik Tjong Kim Sang [email protected]
from tf_ner.
Related Issues (20)
- InvalidArgumentError HOT 1
- Question: Effect of missing word in pre-trained word embeddings on model performance. HOT 1
- Is the evaluation metric the same as the ones in the papers?
- Does this evaluation script apply to BIO or BIES? HOT 1
- The pred_ids of `<pad>` is always zero
- 0 precision 0 recall for some custom tags HOT 2
- Why the result is better than that in the papers? #87 HOT 1
- batch size is creating confusion [ when we compare with Research Paper ]
- tensorflow.contrib.estimator HOT 6
- For models/lstm_crf/main.py, Line 171
- Support for TF 2.0 HOT 6
- InvalidArgumentError: labels contains negative values
- has no attribute 'stop_if_no_increase_hook' for tensorflow 1.9 HOT 1
- Which version of numpy will work HOT 1
- There are issues when I use my own datasets HOT 1
- Thanks for your amazing work!
- Visualizing embeddings & improving accuracy
- In reported result, what is difference between best and abs. best ? Also mean + std. deviation doesnt matches with the best result reported in the github page ? HOT 1
- same result on F1, Accuracy, precision
- Prediction script for single line statements
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from tf_ner.