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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wikiann |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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language: |
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- sk |
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inference: false |
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model-index: |
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- name: fernet-sk-ner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: wikiann sk |
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type: wikiann |
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args: sk |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9359821760118826 |
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- name: Recall |
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type: recall |
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value: 0.9472378804960541 |
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- name: F1 |
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type: f1 |
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value: 0.9415763914830033 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9789063466534702 |
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--- |
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# Named Entity Recognition based on FERNET-CC_sk |
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This model is a fine-tuned version of [fav-kky/FERNET-CC_sk](https://huggingface.co/fav-kky/FERNET-CC_sk) on the Slovak wikiann dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1763 |
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- Precision: 0.9360 |
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- Recall: 0.9472 |
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- F1: 0.9416 |
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- Accuracy: 0.9789 |
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## Intended uses & limitation |
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Supported classes: LOCATION, PERSON, ORGANIZATION |
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``` |
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from transformers import pipeline |
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ner_pipeline = pipeline(task='ner', model='crabz/slovakbert-ner') |
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input_sentence = "Minister financií a líder mandátovo najsilnejšieho hnutia OĽaNO Igor Matovič upozorňuje, že následky tretej vlny budú na Slovensku veľmi veľké." |
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classifications = ner_pipeline(input_sentence) |
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``` |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.1259 | 1.0 | 834 | 0.1095 | 0.8963 | 0.9182 | 0.9071 | 0.9697 | |
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| 0.071 | 2.0 | 1668 | 0.0974 | 0.9270 | 0.9357 | 0.9313 | 0.9762 | |
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| 0.0323 | 3.0 | 2502 | 0.1259 | 0.9257 | 0.9330 | 0.9293 | 0.9745 | |
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| 0.0175 | 4.0 | 3336 | 0.1347 | 0.9241 | 0.9360 | 0.9300 | 0.9756 | |
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| 0.0156 | 5.0 | 4170 | 0.1407 | 0.9337 | 0.9404 | 0.9370 | 0.9780 | |
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| 0.0062 | 6.0 | 5004 | 0.1522 | 0.9267 | 0.9410 | 0.9338 | 0.9774 | |
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| 0.0055 | 7.0 | 5838 | 0.1559 | 0.9322 | 0.9429 | 0.9375 | 0.9780 | |
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| 0.0024 | 8.0 | 6672 | 0.1733 | 0.9321 | 0.9438 | 0.9379 | 0.9779 | |
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| 0.0009 | 9.0 | 7506 | 0.1765 | 0.9347 | 0.9468 | 0.9407 | 0.9784 | |
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| 0.0002 | 10.0 | 8340 | 0.1763 | 0.9360 | 0.9472 | 0.9416 | 0.9789 | |
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### Framework versions |
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- Transformers 4.14.0.dev0 |
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- Pytorch 1.10.0 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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