---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: belajarner
  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

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co./google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2832
- Precision: 0.8019
- Recall: 0.8379
- F1: 0.8195
- Accuracy: 0.9411

## 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: 1e-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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2947        | 1.0   | 1567  | 0.2493          | 0.7364    | 0.7978 | 0.7658 | 0.9276   |
| 0.1966        | 2.0   | 3134  | 0.2276          | 0.7717    | 0.8150 | 0.7927 | 0.9351   |
| 0.1486        | 3.0   | 4701  | 0.2354          | 0.7773    | 0.8293 | 0.8025 | 0.9366   |
| 0.1183        | 4.0   | 6268  | 0.2468          | 0.8001    | 0.8388 | 0.8190 | 0.9396   |
| 0.096         | 5.0   | 7835  | 0.2539          | 0.8093    | 0.8296 | 0.8193 | 0.9407   |
| 0.0772        | 6.0   | 9402  | 0.2717          | 0.8000    | 0.8382 | 0.8187 | 0.9395   |
| 0.0648        | 7.0   | 10969 | 0.2822          | 0.8010    | 0.8400 | 0.8201 | 0.9412   |
| 0.0556        | 8.0   | 12536 | 0.2832          | 0.8019    | 0.8379 | 0.8195 | 0.9411   |


### Framework versions

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