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bart-cnn-large-xsum – AI Model by bmaruyama | AlphaNeural AI
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bmaruyama
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bart-cnn-large-xsum
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transformers
tensorboard
safetensors
bart
text2text-generation
generated_from_trainer
xsum
facebook/bart-large-cnn
finetune
mit
endpoints_compatible
us
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bart-cnn-large-xsum
This model is a fine-tuned version of
facebook/bart-large-cnn
on the xsum dataset. It achieves the following results on the evaluation set:
Loss: 0.0698
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
0.0692
1.0
256
0.0698
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cpu
Datasets 2.18.0
Tokenizers 0.15.2
