|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- wikiann |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
inference: false |
|
language: |
|
- sk |
|
model-index: |
|
- name: bertoslav-limited-ner |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: wikiann sk |
|
type: wikiann |
|
args: sk |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.8985571260306242 |
|
- name: Recall |
|
type: recall |
|
value: 0.9173994738819993 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9078805459481573 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9700235061239639 |
|
--- |
|
|
|
# Named Entity Recognition based on bertoslav-limited |
|
|
|
This model is a fine-tuned version of [crabz/bertoslav-limited](https://huggingface.co/crabz/bertoslav-limited) on the Slovak wikiann dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2119 |
|
- Precision: 0.8986 |
|
- Recall: 0.9174 |
|
- F1: 0.9079 |
|
- Accuracy: 0.9700 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.2953 | 1.0 | 834 | 0.1516 | 0.8413 | 0.8647 | 0.8529 | 0.9549 | |
|
| 0.0975 | 2.0 | 1668 | 0.1304 | 0.8787 | 0.9056 | 0.8920 | 0.9658 | |
|
| 0.0487 | 3.0 | 2502 | 0.1405 | 0.8916 | 0.8958 | 0.8937 | 0.9660 | |
|
| 0.025 | 4.0 | 3336 | 0.1658 | 0.8850 | 0.9116 | 0.8981 | 0.9669 | |
|
| 0.0161 | 5.0 | 4170 | 0.1739 | 0.8974 | 0.9127 | 0.9050 | 0.9693 | |
|
| 0.0074 | 6.0 | 5004 | 0.1888 | 0.8900 | 0.9144 | 0.9020 | 0.9687 | |
|
| 0.0051 | 7.0 | 5838 | 0.1996 | 0.8946 | 0.9145 | 0.9044 | 0.9693 | |
|
| 0.0039 | 8.0 | 6672 | 0.2052 | 0.8993 | 0.9158 | 0.9075 | 0.9697 | |
|
| 0.0024 | 9.0 | 7506 | 0.2112 | 0.8946 | 0.9171 | 0.9057 | 0.9696 | |
|
| 0.0018 | 10.0 | 8340 | 0.2119 | 0.8986 | 0.9174 | 0.9079 | 0.9700 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.14.0.dev0 |
|
- Pytorch 1.10.0 |
|
- Datasets 1.16.1 |
|
- Tokenizers 0.10.3 |
|
|
