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Sinhala_Bert_Finetune_BS8_LR2e-5
GeethmaYasashwi/Sinhala_Bert_Finetune_BS8_LR2e-5
Sinhala_Bert_Finetune_BS8_LR2e-5 is a machine learning model from GeethmaYasashwi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- encoder-decoder
- Access
- Public
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026
- SHA
- e6fd38df
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. -->
Sinhala_Bert_Finetune_BS8_LR2e-5
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1821
- Bleu: 0.4279
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: 16
- eval_batch_size: 16
- seed: 42
- 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: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 6.9549 | 1.0 | 225 | 3.1586 | 2.0557 |
| 4.9197 | 2.0 | 450 | 2.5200 | 2.5634 |
| 4.1109 | 3.0 | 675 | 2.1008 | 3.8007 |
| 3.2783 | 4.0 | 900 | 1.7975 | 13.5566 |
| 2.4474 | 5.0 | 1125 | 1.5934 | 22.6077 |
| 1.8907 | 6.0 | 1350 | 1.4460 | 29.8262 |
| 1.6821 | 7.0 | 1575 | 1.3480 | 32.6221 |
| 1.2704 | 8.0 | 1800 | 1.2910 | 31.4855 |
| 1.1577 | 9.0 | 2025 | 1.2595 | 42.7246 |
| 0.9222 | 10.0 | 2250 | 1.2180 | 40.0441 |
| 0.7346 | 11.0 | 2475 | 1.1746 | 44.1229 |
| 0.6097 | 12.0 | 2700 | 1.1689 | 47.3475 |
| 0.6070 | 13.0 | 2925 | 1.1767 | 42.2465 |
| 0.4839 | 14.0 | 3150 | 1.1435 | 48.0279 |
| 0.4263 | 15.0 | 3375 | 1.1408 | 49.9589 |
| 0.3260 | 16.0 | 3600 | 1.1362 | 53.3992 |
| 0.2929 | 17.0 | 3825 | 1.1412 | 51.4126 |
| 0.2679 | 18.0 | 4050 | 1.1183 | 57.0391 |
| 0.2498 | 19.0 | 4275 | 1.1279 | 56.6146 |
| 0.1969 | 20.0 | 4500 | 1.1325 | 56.9288 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2
- Library
- transformers
- Type
- encoder-decoder
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026