---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: SingPurcBERT-Katch-0328
  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. -->

# SingPurcBERT-Katch-0328

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: 0.4296
- Accuracy: 0.8593
- F1: 0.8593

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.384         | 1.0   | 3372  | 0.3757          | 0.8450   | 0.8445 |
| 0.3444        | 2.0   | 6744  | 0.3650          | 0.8583   | 0.8583 |
| 0.3386        | 3.0   | 10116 | 0.4296          | 0.8593   | 0.8593 |
| 0.3166        | 4.0   | 13488 | 0.5125          | 0.8460   | 0.8457 |
| 0.2781        | 5.0   | 16860 | 0.7211          | 0.8504   | 0.8502 |
| 0.2236        | 6.0   | 20232 | 0.7112          | 0.8504   | 0.8503 |
| 0.2008        | 7.0   | 23604 | 0.8183          | 0.8509   | 0.8509 |
| 0.1591        | 8.0   | 26976 | 0.9926          | 0.8464   | 0.8462 |
| 0.1103        | 9.0   | 30348 | 1.0597          | 0.8411   | 0.8409 |
| 0.0802        | 10.0  | 33720 | 1.0660          | 0.8436   | 0.8436 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1