---
library_name: transformers
base_model: rmtariq/malay_classification
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: malay_classification
  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. -->

# malay_classification

This model is a fine-tuned version of [rmtariq/malay_classification](https://huggingface.co/rmtariq/malay_classification) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1691        | 0.2720 | 500  | 0.1373          | 0.9717   | 0.9717 | 0.9730    | 0.9717 |
| 0.0493        | 0.5441 | 1000 | 0.0369          | 0.9943   | 0.9943 | 0.9945    | 0.9943 |
| 0.0669        | 0.8161 | 1500 | 0.0406          | 0.9952   | 0.9952 | 0.9954    | 0.9952 |
| 0.0287        | 1.0881 | 2000 | 0.0276          | 0.9943   | 0.9944 | 0.9948    | 0.9943 |
| 0.0061        | 1.3602 | 2500 | 0.0168          | 0.9971   | 0.9971 | 0.9972    | 0.9971 |
| 0.0137        | 1.6322 | 3000 | 0.0128          | 0.9981   | 0.9981 | 0.9981    | 0.9981 |
| 0.0178        | 1.9042 | 3500 | 0.0179          | 0.9968   | 0.9968 | 0.9969    | 0.9968 |
| 0.0112        | 2.1763 | 4000 | 0.0110          | 0.9975   | 0.9975 | 0.9975    | 0.9975 |
| 0.0001        | 2.4483 | 4500 | 0.0079          | 0.9987   | 0.9987 | 0.9988    | 0.9987 |
| 0.0001        | 2.7203 | 5000 | 0.0021          | 0.9987   | 0.9987 | 0.9987    | 0.9987 |
| 0.0003        | 2.9924 | 5500 | 0.0024          | 0.9990   | 0.9990 | 0.9991    | 0.9990 |


### Framework versions

- Transformers 4.53.1
- Pytorch 2.7.1
- Datasets 3.6.0
- Tokenizers 0.21.2