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bart-large-cnn-ing-extraction – AI Model by theojolliffe | AlphaNeural AI
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theojolliffe
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bart-large-cnn-ing-extraction
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transformers
pytorch
tensorboard
bart
text2text-generation
generated_from_trainer
mit
endpoints_compatible
us
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bart-large-cnn-ing-extraction
This model is a fine-tuned version of
facebook/bart-large-cnn
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.8043
Rouge1: 10.4409
Rouge2: 3.3584
Rougel: 10.3769
Rougelsum: 10.3943
Gen Len: 57.7443
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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
0.1692
1.0
762
1.8043
10.4409
3.3584
10.3769
10.3943
57.7443
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
