
# 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

{"language": ["sk"], "license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["wikiann"], "metrics": ["precision", "recall", "f1", "accuracy"], "inference": false, "model-index": [{"name": "fernet-sk-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "wikiann sk", "type": "wikiann", "args": "sk"}, "metrics": [{"type": "precision", "value": 0.9359821760118826, "name": "Precision"}, {"type": "recall", "value": 0.9472378804960541, "name": "Recall"}, {"type": "f1", "value": 0.9415763914830033, "name": "F1"}, {"type": "accuracy", "value": 0.9789063466534702, "name": "Accuracy"}]}]}]}
transformers pytorch bert token-classification generated_from_trainer sk dataset:wikiann license:cc-by-nc-sa-4.0 model-index autotrain_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #sk #dataset-wikiann #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #region-us 

Named Entity Recognition based on FERNET-CC\_sk
===============================================


This model is a fine-tuned version of 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


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



### Framework versions


* Transformers 4.14.0.dev0
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3



### 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 ### Framework versions


* Transformers 4.14.0.dev0
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #sk #dataset-wikiann #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.14.0.dev0
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #sk #dataset-wikiann #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #region-us 
### 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### Framework versions


* Transformers 4.14.0.dev0
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3