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---
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
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