---
license: afl-3.0
base_model: Davlan/bert-base-multilingual-cased-ner-hrl
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: belajarner_bert_case
  results: []
---

<!-- 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. -->

# belajarner_bert_case

This model is a fine-tuned version of [Davlan/bert-base-multilingual-cased-ner-hrl](https://huggingface.co/Davlan/bert-base-multilingual-cased-ner-hrl) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3367
- Precision: 0.8139
- Recall: 0.8422
- F1: 0.8278
- Accuracy: 0.9420

## 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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2503        | 1.0   | 1567  | 0.2331          | 0.7484    | 0.8148 | 0.7802 | 0.9294   |
| 0.1645        | 2.0   | 3134  | 0.2307          | 0.7987    | 0.8158 | 0.8072 | 0.9363   |
| 0.1097        | 3.0   | 4701  | 0.2588          | 0.7764    | 0.8334 | 0.8039 | 0.9360   |
| 0.0822        | 4.0   | 6268  | 0.2624          | 0.8056    | 0.8389 | 0.8219 | 0.9409   |
| 0.061         | 5.0   | 7835  | 0.2927          | 0.8183    | 0.8275 | 0.8229 | 0.9414   |
| 0.0407        | 6.0   | 9402  | 0.3156          | 0.8021    | 0.8350 | 0.8182 | 0.9399   |
| 0.0315        | 7.0   | 10969 | 0.3257          | 0.8102    | 0.8381 | 0.8239 | 0.9413   |
| 0.0238        | 8.0   | 12536 | 0.3367          | 0.8139    | 0.8422 | 0.8278 | 0.9420   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2