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Fine-tuning – AI Model by Nikhil-bv | AlphaNeural AI
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Nikhil-bv
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Fine-tuning
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
facebook/bart-large-cnn
finetune
mit
endpoints_compatible
us
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Fine-tuning
This model is a fine-tuned version of
facebook/bart-large-cnn
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2566
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: 1e-05
train_batch_size: 8
eval_batch_size: 8
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
0.1547
1.0
37
0.2688
0.1362
2.0
74
0.2566
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
