|
--- |
|
license: apache-2.0 |
|
base_model: bert-base-multilingual-cased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- id_nergrit_corpus |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: bert-base-multilingual-cased-ner-silvanus |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: id_nergrit_corpus |
|
type: id_nergrit_corpus |
|
config: ner |
|
split: validation |
|
args: ner |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.9068952084144917 |
|
- name: Recall |
|
type: recall |
|
value: 0.9201581027667984 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9134785167745734 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9851764523984384 |
|
--- |
|
|
|
<!-- 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-base-multilingual-cased-ner-silvanus |
|
|
|
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the id_nergrit_corpus dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0621 |
|
- Precision: 0.9069 |
|
- Recall: 0.9202 |
|
- F1: 0.9135 |
|
- Accuracy: 0.9852 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.1336 | 1.0 | 827 | 0.0551 | 0.9034 | 0.9130 | 0.9082 | 0.9844 | |
|
| 0.0461 | 2.0 | 1654 | 0.0604 | 0.9098 | 0.9134 | 0.9116 | 0.9842 | |
|
| 0.0299 | 3.0 | 2481 | 0.0621 | 0.9069 | 0.9202 | 0.9135 | 0.9852 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
