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---
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
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