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See http://github.com/onurgu/joint-ner-and-md-tagger This repository is basically a Bi-LSTM based sequence tagger in both Tensorflow and Dynet which can utilize several sources of information about each word unit like word embeddings, character based embeddings and morphological tags from an FST to obtain the representation for that specific word unit.

License: MIT License

Python 30.39% Perl 2.97% sed 59.07% Shell 5.46% Awk 0.19% Jupyter Notebook 1.91%
bi-lstm dynet named-entity-recognition neural-networks reimplementation sequence-tagger tensorflow

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ner-tagger-dynet's Issues

About the meaning of outputs

Firstly, I would like to say thanks to you for your sharing.
When I ran training file: 'train_tensorflow.py' I got negative numbers that I don't understand what they mean?
Starting epoch 5...
Reshuffling
n_batches: 29
bucket_id: 7
-8.567176 -7.873434 -7.972278 n_batches: 29
Reshuffling
bucket_id: 5
-7.769209 -7.041025 -6.468853 Reshuffling
n_batches: 29

Could you mind explaining for me? where is the accuracy, Precision, Recall, F1 on training set, dev set?
Thank you in advance!

P.s: I also ran source code given by Lample et al, and here is output:
processed 8843 tokens with 388 phrases; found: 332 phrases; correct: 243.
accuracy: 96.57%; precision: 73.19%; recall: 62.63%; FB1: 67.50
ORG: precision: 73.09%; recall: 64.54%; FB1: 68.55 249
PER: precision: 73.49%; recall: 57.55%; FB1: 64.55 83
ID NE Total O I-ORG B-ORG B-PER I-PER Percent
0 O 8015 7942 28 27 9 9 99.089
1 I-ORG 357 66 277 7 0 7 77.591
2 B-ORG 282 63 13 194 12 0 68.794
3 B-PER 106 15 2 21 62 6 58.491
4 I-PER 83 5 13 0 0 65 78.313
8540/8843 (96.57356%)
Score on dev: 67.46000
Score on test: 67.50000
New best score on dev.

creation of eval log folder

./evaluation/temp/eval_logs is not created automatically which stops the training
with an error message something similar to below during evaluation:
IOError: [Errno 2] No such file or directory: './evaluation/temp/eval_logs/dev.eval.1212048.epoch-0000.output'

When I train first model, It does not create mappings.pkl

in model_tensorflow.save_mappings

if overwrite_mappings is off(0) and the mapping file does not exists,
It does not create new one.

So the flow must be like

if not exists(mapping_file):
    create_one()
else:
    if overwrite_option:
        create_one()
    else:
        #handle_unexpected_behaviour
        #or dismiss?

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