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BART_Summary – AI Model by whismyswift | AlphaNeural AI
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BART_Summary
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peft
safetensors
adapter
lora
transformers
facebook/bart-base
apache-2.0
us
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BART_Summary
This model is a fine-tuned version of
facebook/bart-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.2050
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: 3e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
135
2.3946
No log
2.0
270
2.2867
No log
3.0
405
2.2371
5.5684
4.0
540
2.2109
5.5684
5.0
675
2.2050
Framework versions
PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
