tags: | |
- generated_from_trainer | |
datasets: | |
- wikiann | |
metrics: | |
- precision | |
- recall | |
- f1 | |
- accuracy | |
model-index: | |
- name: BERT_swedish-ner | |
results: | |
- task: | |
name: Token Classification | |
type: token-classification | |
dataset: | |
name: wikiann | |
type: wikiann | |
config: sv | |
split: train | |
args: sv | |
metrics: | |
- name: Precision | |
type: precision | |
value: 0.9340386115444618 | |
- name: Recall | |
type: recall | |
value: 0.9418907624993855 | |
- name: F1 | |
type: f1 | |
value: 0.9379482534942355 | |
- name: Accuracy | |
type: accuracy | |
value: 0.979997105690534 | |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
should probably proofread and complete it, then remove this comment. --> | |
# BERT_swedish-ner | |
This model is a fine-tuned version of [KB/bert-base-swedish-cased](https://huggingface.co/KB/bert-base-swedish-cased) on the wikiann dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.1316 | |
- Precision: 0.9340 | |
- Recall: 0.9419 | |
- F1: 0.9379 | |
- Accuracy: 0.9800 | |
## Model description | |
More information needed | |
## Intended uses & limitations | |
More information needed | |
## Training and evaluation data | |
More information needed | |
## Training procedure | |
### Training hyperparameters | |
The following hyperparameters were used during training: | |
- learning_rate: 5e-05 | |
- train_batch_size: 12 | |
- eval_batch_size: 12 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 5 | |
### Training results | |
### Framework versions | |
- Transformers 4.22.1 | |
- Pytorch 1.12.1+cu113 | |
- Datasets 2.4.0 | |
- Tokenizers 0.12.1 | |