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mbart-sinhala-summarization – AI Model by MVeeW | AlphaNeural AI
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mbart-sinhala-summarization
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transformers
tensorboard
safetensors
mbart
text2text-generation
generated_from_trainer
facebook/mbart-large-50
finetune
mit
endpoints_compatible
us
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mbart-sinhala-summarization
This model is a fine-tuned version of
facebook/mbart-large-50
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7119
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: 2
eval_batch_size: 2
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.8444
1.0
1625
0.6918
0.6061
2.0
3250
0.6834
0.4733
3.0
4875
0.7119
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
