---
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: 0.3309
- Precision: 0.8120
- Recall: 0.8430
- F1: 0.8272
- Accuracy: 0.9423

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2528        | 1.0   | 1567  | 0.2352          | 0.7442    | 0.8116 | 0.7765 | 0.9282   |
| 0.1653        | 2.0   | 3134  | 0.2250          | 0.8008    | 0.8218 | 0.8112 | 0.9378   |
| 0.1125        | 3.0   | 4701  | 0.2545          | 0.7703    | 0.8381 | 0.8028 | 0.9343   |
| 0.083         | 4.0   | 6268  | 0.2633          | 0.8065    | 0.8353 | 0.8206 | 0.9401   |
| 0.0602        | 5.0   | 7835  | 0.2860          | 0.8124    | 0.8229 | 0.8176 | 0.9413   |
| 0.0411        | 6.0   | 9402  | 0.3129          | 0.8026    | 0.8353 | 0.8186 | 0.9404   |
| 0.0324        | 7.0   | 10969 | 0.3180          | 0.8036    | 0.8400 | 0.8214 | 0.9418   |
| 0.0248        | 8.0   | 12536 | 0.3309          | 0.8120    | 0.8430 | 0.8272 | 0.9423   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2