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bart-cnn-science-v3-e2 – AI Model by theojolliffe | AlphaNeural AI
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theojolliffe
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bart-cnn-science-v3-e2
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transformers
pytorch
tensorboard
bart
text2text-generation
generated_from_trainer
mit
endpoints_compatible
us
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bart-cnn-science-v3-e2
This model is a fine-tuned version of
theojolliffe/bart-cnn-science
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.9352
Rouge1: 52.5497
Rouge2: 32.5507
Rougel: 35.0014
Rougelsum: 50.0575
Gen Len: 141.5741
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: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
No log
1.0
398
1.0023
52.0744
31.917
33.2804
49.6569
142.0
1.1851
2.0
796
0.9352
52.5497
32.5507
35.0014
50.0575
141.5741
Framework versions
Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1
