generated_from_trainer

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outputs

This model is a fine-tuned version of gerulata/slovakbert on the ju-bezdek/conll2003-SK-NER dataset. It achieves the following results on the evaluation (validation) set:

Model description

More information needed

Code example

from transformers import pipeline, AutoModel, AutoTokenizer
from spacy import displacy
import os


model_path="ju-bezdek/slovakbert-conll2003-sk-ner"

aggregation_strategy="max"
ner_pipeline = pipeline(task='ner', model=model_path, aggregation_strategy=aggregation_strategy)

input_sentence= "Ruský premiér Viktor Černomyrdin v piatok povedal, že prezident Boris Jeľcin , ktorý je na dovolenke mimo Moskvy , podporil mierový plán šéfa bezpečnosti Alexandra Lebedu pre Čečensko, uviedla tlačová agentúra Interfax"
ner_ents = ner_pipeline(input_sentence)
print(ner_ents)

ent_group_labels = [ner_pipeline.model.config.id2label[i][2:] for i in ner_pipeline.model.config.id2label if i>0]

options = {"ents":ent_group_labels}

dicplacy_ents = [{"start":ent["start"], "end":ent["end"], "label":ent["entity_group"]} for ent in ner_ents]
displacy.render({"text":input_sentence, "ents":dicplacy_ents}, style="ent", options=options, jupyter=True, manual=True)

Result:

<div> <span class="tex2jax_ignore"><div class="entities" style="line-height: 2.5; direction: ltr"> <mark class="entity" style="background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;"> Ruský <span style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem">MISC</span> </mark> premiér <mark class="entity" style="background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;"> Viktor Černomyrdin <span style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem">PER</span> </mark> v piatok povedal, že prezident <mark class="entity" style="background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;"> Boris Jeľcin, <span style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem">PER</span> </mark> , ktorý je na dovolenke mimo <mark class="entity" style="background: #ff9561; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;"> Moskvy <span style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem">LOC</span> </mark> , podporil mierový plán šéfa bezpečnosti <mark class="entity" style="background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;"> Alexandra Lebedu <span style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem">PER</span> </mark> pre <mark class="entity" style="background: #ff9561; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;"> Čečensko, <span style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem">LOC</span> </mark> uviedla tlačová agentúra <mark class="entity" style="background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;"> Interfax <span style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem">ORG</span> </mark> </div></span> </div>

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.3237 1.0 878 0.2541 0.7125 0.8059 0.7563 0.9283
0.1663 2.0 1756 0.2370 0.7775 0.8090 0.7929 0.9394
0.1251 3.0 2634 0.2289 0.7732 0.8029 0.7878 0.9385
0.0984 4.0 3512 0.2818 0.7294 0.8189 0.7715 0.9294
0.0808 5.0 4390 0.3138 0.7615 0.7900 0.7755 0.9326
0.0578 6.0 5268 0.3072 0.7548 0.8222 0.7871 0.9370
0.0481 7.0 6146 0.2778 0.7897 0.8156 0.8025 0.9408
0.0414 8.0 7024 0.3336 0.7695 0.8201 0.7940 0.9389
0.0268 9.0 7902 0.3294 0.7868 0.8140 0.8002 0.9409
0.0204 10.0 8780 0.3693 0.7657 0.8239 0.7938 0.9376
0.016 11.0 9658 0.3816 0.7932 0.8242 0.8084 0.9425
0.0108 12.0 10536 0.3607 0.7929 0.8256 0.8089 0.9431
0.0078 13.0 11414 0.3980 0.7915 0.8240 0.8074 0.9423
0.0062 14.0 12292 0.4096 0.7995 0.8247 0.8119 0.9436
0.0035 15.0 13170 0.4177 0.8006 0.8251 0.8127 0.9438

Framework versions