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easyTermsSummerizer – AI Model by Quake24 | AlphaNeural AI
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Quake24
/
easyTermsSummerizer
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transformers
pytorch
tensorboard
bart
text2text-generation
summarization
generated_from_trainer
en
Quake24/paraphrasedPayPal
Quake24/paraphrasedTwitter
apache-2.0
endpoints_compatible
us
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Model card
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easyTermsSummerizer
This model is a fine-tuned version of
sshleifer/distilbart-cnn-12-6
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.8124
Rouge1: 0.7533
Rouge2: 0.6964
Rougel: 0.6806
Rougelsum: 0.6793
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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
No log
1.0
2
2.2083
0.7332
0.6595
0.6374
0.6376
No log
2.0
4
1.9331
0.7776
0.7268
0.6991
0.7005
No log
3.0
6
1.8124
0.7533
0.6964
0.6806
0.6793
Framework versions
Transformers 4.27.3
Pytorch 1.13.0
Datasets 2.1.0
Tokenizers 0.13.2
