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xlmr-singlish-sinhala-lora – AI Model by RukDias | AlphaNeural AI
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RukDias
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xlmr-singlish-sinhala-lora
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peft
safetensors
adapter
lora
transformers
deshanksuman/swaBhahsa_XLMR_Transliteration
apache-2.0
us
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xlmr-singlish-sinhala-lora
This model is a fine-tuned version of
deshanksuman/swaBhahsa_XLMR_Transliteration
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1686
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: 0.0001
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.8855
1.0
313
0.1984
0.7692
2.0
626
0.1824
0.6254
3.0
939
0.1742
0.6276
4.0
1252
0.1704
0.5605
5.0
1565
0.1686
Framework versions
PEFT 0.18.1
Transformers 5.1.0
Pytorch 2.7.1+cu118
Datasets 4.5.0
Tokenizers 0.22.2
