---
license: gpl-3.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: test3
  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. -->

# test3

This model is a fine-tuned version of [jcblaise/bert-tagalog-base-cased](https://huggingface.co/jcblaise/bert-tagalog-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3960
- Accuracy: 0.8683
- Precision: 0.8316
- Recall: 0.8653
- F1: 0.8481

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 151  | 0.3770          | 0.8431   | 0.8287    | 0.7951 | 0.8115 |
| No log        | 2.0   | 302  | 0.3561          | 0.8528   | 0.7959    | 0.8790 | 0.8354 |
| No log        | 3.0   | 453  | 0.3425          | 0.8647   | 0.8636    | 0.8094 | 0.8356 |
| 0.3579        | 4.0   | 604  | 0.3541          | 0.8615   | 0.8090    | 0.8824 | 0.8441 |
| 0.3579        | 5.0   | 755  | 0.3717          | 0.8611   | 0.8075    | 0.8836 | 0.8438 |
| 0.3579        | 6.0   | 906  | 0.3657          | 0.8691   | 0.8352    | 0.8619 | 0.8483 |
| 0.1703        | 7.0   | 1057 | 0.3826          | 0.8700   | 0.8370    | 0.8619 | 0.8493 |
| 0.1703        | 8.0   | 1208 | 0.3960          | 0.8683   | 0.8316    | 0.8653 | 0.8481 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2