metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: khmer-sentence-segmentation
results: []
khmer-sentence-segmentation
This model is a fine-tuned version of 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