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bart-news-summarizer – AI Model by Youssef-El-SaYed | AlphaNeural AI
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Youssef-El-SaYed
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bart-news-summarizer
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transformers
tensorboard
safetensors
bart
text2text-generation
generated_from_trainer
facebook/bart-base
finetune
apache-2.0
endpoints_compatible
us
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bart-news-summarizer
This model is a fine-tuned version of
facebook/bart-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.0816
Rouge1: 39.04
Rouge2: 16.93
Rougel: 26.06
Rougelsum: 26.11
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: 10
eval_batch_size: 10
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: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
No log
1.0
144
1.1131
40.25
18.58
27.58
27.57
No log
2.0
288
1.0992
40.16
18.49
27.66
27.68
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2
