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