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byt5-base-khm-en
Darayut/byt5-base-khm-en
byt5-base-khm-en is a translation model from Darayut. Use it when you need text moved from one language to another. 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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At a glance
- Task
- Translation
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Jan 20, 2026
- Updated
- Jan 21, 2026
- SHA
- a12335d7
Base models
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. -->
byt5-base-khm-en
This model is a fine-tuned version of google/byt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5602
- Bleu: 26.8820
- Gen Len: 23.5353
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: 0.0003
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Additional Training includes the Asian Language Treebank (ALT) Dataset
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: Cosine
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.8053 | 1.0 | 1333 | 0.9467 | 3.0623 | 34.1781 |
| 0.6026 | 2.0 | 2666 | 0.7041 | 12.6402 | 26.6596 |
| 0.4719 | 3.0 | 3999 | 0.5933 | 17.5698 | 24.2143 |
| 0.4029 | 4.0 | 5332 | 0.5593 | 22.9685 | 24.0115 |
| 0.3404 | 5.0 | 6665 | 0.5602 | 26.8820 | 23.5353 |
| 0.5988 | 6.0 | 7998 | 0.5456 | 17.1649 | 78.2938 |
| 0.4947 | 7.0 | 9331 | 0.4823 | 20.9237 | 81.6542 |
| 0.4402 | 8.0 | 10664 | 0.4455 | 25.0764 | 75.5452 |
Evaluation results
The evaluation is done on the Tatoeba and Asian Language Treebank (ALT) dataset.
| Metrics | Value |
|---|---|
| BLEU | 25.08 |
| chrF | 50.05 |
| BERTScore F1 | 0.9356 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1
- Task
- Translation
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Languages
- km, en
- Created
- Jan 20, 2026
- Updated
- Jan 21, 2026