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khmer-text-classification-roberta
seanghay/khmer-text-classification-roberta
khmer-text-classification-roberta is a text classification model from seanghay. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Model card
From the Hugging Face model README
<!-- 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-text-classification-roberta
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8290
- Accuracy: 0.6477
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: 44
- eval_batch_size: 44
- 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 | Accuracy |
|---|---|---|---|---|
| 0.983 | 1.0 | 1228 | 0.8927 | 0.6327 |
| 0.8734 | 2.0 | 2456 | 0.8639 | 0.6417 |
| 0.8008 | 3.0 | 3684 | 0.8296 | 0.648 |
| 0.7483 | 4.0 | 4912 | 0.8290 | 0.6477 |
Framework versions
- Transformers 4.29.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- apache-2.0
- Languages
- km
- Created
- May 13, 2023
- Updated
- May 14, 2023