---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: khmer-sentence-segmentation
  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. -->

# khmer-sentence-segmentation

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1784
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9266

## 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: 24
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.1963        | 1.0   | 1390 | 0.1842          | 0.0       | 0.0    | 0.0 | 0.9222   |
| 0.1749        | 2.0   | 2780 | 0.1816          | 0.0       | 0.0    | 0.0 | 0.9251   |
| 0.1629        | 3.0   | 4170 | 0.1775          | 0.0       | 0.0    | 0.0 | 0.9264   |
| 0.1521        | 4.0   | 5560 | 0.1784          | 0.0       | 0.0    | 0.0 | 0.9266   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3