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bart-nepalix – AI Model by kiranpantha | AlphaNeural AI
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kiranpantha
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bart-nepalix
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transformers
tensorboard
safetensors
bart
text2text-generation
generated_from_trainer
endpoints_compatible
us
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bart-nepalix
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1123
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: 150
eval_batch_size: 150
seed: 42
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
0.4394
1.0
2917
0.3637
0.2527
2.0
5834
0.2022
0.1766
3.0
8751
0.1442
0.162
4.0
11668
0.1205
0.1366
5.0
14585
0.1123
Framework versions
Transformers 4.47.1
Pytorch 2.6.0+xpu
Datasets 3.2.0
Tokenizers 0.21.0
